Python Data Analytics Jobs

GCP Data Engineer

SACHA Engineering•

Chennai

•Full-time

Job Summary We are seeking a skilled and experienced GCP Data Engineer to join our growing team in Chennai. This role is critical to building and maintaining our data infrastructure, ensuring data quality, and enabling data-driven decision-making across the organization. The ideal candidate will possess a strong foundation in data engineering principles and a proven ability to work with cloud-based technologies, specifically the GCP platform. Key Responsibilities The GCP Data Engineer will be responsible for the following: Designing, building, and maintaining robust and scalable data pipelines using ETL processes. Developing and implementing data quality checks and validation procedures to ensure data accuracy and reliability. Ingesting data from various sources, including APIs and databases, into our GCP environment. Performing Data Mining and Data Analytics to identify trends and insights. Collaborating with cross-functional teams to understand data requirements and deliver effective data solutions. Utilizing Git version control for code management and collaboration. Developing and maintaining RESTful APIs for data access and integration. Required Skills & Qualifications To be successful in this role, candidates must possess the following skills and qualifications: Proficiency in Data Engineering principles and practices. Strong experience with BI Tools for data visualization and reporting. Expertise in SQL for data querying and manipulation. Solid programming skills in Python for data processing and automation. Experience with API Development , including designing and implementing RESTful APIs . Hands-on experience with GCP services for data storage, processing, and analytics. Familiarity with Data Integration techniques and tools. Understanding of Data Quality principles and methodologies. Experience with Data Ingestion from various sources. Proficiency in using Git version control for collaborative code management. Experience Required: 5 - 10 years of relevant experience in data engineering, demonstrating a strong track record of building and maintaining data pipelines and working with cloud technologies. This level of experience indicates a senior-level role requiring independent problem-solving and the ability to mentor junior team members. What We Offer Salary:

Python Data Analytics

SACHA Engineering•

Chennai

•Full-time

Job Summary We are seeking a skilled Python Data Analytics professional to join our team in Chennai. This role offers an exciting opportunity to contribute to a dynamic environment within the IT / Technology industry. Key Responsibilities This role will involve a range of responsibilities centered around data analysis and reporting, leveraging Python and related technologies to extract meaningful insights from complex datasets. The successful candidate will be expected to demonstrate a strong ability to translate data into actionable recommendations. Required Skills & Qualifications Python : Proficiency in Python programming is essential, including experience in developing and implementing data analysis scripts and algorithms. Data Analytics : A strong foundation in Data Analytics principles and techniques, with the ability to apply these to real-world business problems. Big Data Query : Experience with Big Data Query techniques and tools to efficiently process and analyze large datasets. GCP : Familiarity with GCP (Google Cloud Platform) for data storage, processing, and analysis. Github : Experience using Github for version control and collaborative development. Pandas : Expertise in using Pandas for data manipulation and analysis. NumPy : Proficiency in utilizing NumPy for numerical computations and array processing. SciPy : Knowledge of SciPy for scientific computing and statistical analysis. Dask : Experience with Dask for parallel computing and scaling data analysis tasks. Hadoop : Understanding of Hadoop ecosystem for distributed data storage and processing. Hive : Experience with Hive for querying and analyzing data stored in Hadoop . Spark : Proficiency in using Spark for fast and scalable data processing. Data Retrieval : Ability to retrieve data from various sources and formats. Data Processing : Strong skills in data cleaning, transformation, and preparation for analysis. RESTful Web APIs : Understanding of RESTful Web APIs for data integration and exchange. Data Sources : Ability to connect to and extract data from diverse Data Sources . Windows & Linux : Comfortable working in both Windows and Linux environments. Written Communication Skills : Excellent Written Communication Skills for creating clear and concise reports and documentation. Verbal Communication Skills : Strong Verbal Communication Skills for presenting findings and collaborating with stakeholders. Organizational Skills : Demonstrated Organizational Skills for managing multiple tasks and priorities effectively. Attention to Detail : A meticulous Attention to Detail to ensure data accuracy and integrity. Multi-tasking Skills : Ability to effectively manage and prioritize multiple tasks simultaneously. Reporting Tools : Experience with various Reporting Tools for creating insightful visualizations and dashboards. Metrics : Understanding of key performance indicators ( Metrics ) and their application in data analysis. Visualizations : Ability to create compelling Visualizations to communicate data insights effectively. Software Traceability : Knowledge of Software Traceability principles and practices. Documentation : Ability to create comprehensive and accurate Documentation for data analysis processes and results. Experience Required: The ideal candidate will possess 4 - 8 years of relevant experience in a data analytics role, demonstrating a proven ability to deliver impactful insights and solve complex business problems. This level of experience indicates a level of seniority requiring independent work and mentorship capabilities. What We Offer Salary:

Quality Data Analyst – Electrical Hardware Engineering, Warranty Analytics | KPI Automation | Design Assessment | AI Adoption

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a skilled and experienced Quality Data Analyst to join our team. This role will focus on leveraging data analysis and advanced techniques to support our Electrical Hardware Engineering, Warranty Analytics, KPI Automation, Design Assessment, and AI Adoption initiatives within the Automotive / Technology industry. The ideal candidate will possess a strong analytical background and a passion for driving data-driven decisions. Key Responsibilities This role will be responsible for a range of tasks including data analysis, visualization, and reporting to support quality initiatives. The candidate will be expected to identify trends, anomalies, and opportunities for improvement within warranty data, cost trends, and design performance. They will also be involved in the automation of KPI reporting and the implementation of AI -assisted analytics to enhance predictive quality and drive corrective action management . Required Skills & Qualifications Data Analysis: Demonstrated ability to extract, clean, and analyze large datasets to identify meaningful insights and trends. Data Visualization: Proficiency in creating compelling and informative data visualizations using tools such as Power BI and Excel Analytics to communicate complex information effectively. Dashboarding & KPI Reporting: Experience in designing and developing interactive dashboards and automated KPI reports to track key performance indicators and monitor quality metrics. Data Storytelling: Ability to translate data insights into clear and concise narratives that resonate with stakeholders and drive informed decision-making. SQL: Strong proficiency in SQL for data extraction, manipulation, and analysis. Python: Experience using Python for data analysis, scripting, and automation. Databricks: Familiarity with Databricks for data processing and analytics. Power Automate: Experience with Power Automate for workflow automation and data integration. Warranty Data Analytics: Expertise in analyzing warranty data to identify root causes of failures, predict future trends, and optimize product designs. Cost Trend Analysis: Ability to analyze cost trends to identify areas for cost reduction and process improvement. KPI Automation: Experience in automating KPI reporting and data collection processes. Multi-Source Data Integration: Ability to integrate data from multiple sources to create a comprehensive view of quality performance. AI-Assisted Analytics: Experience leveraging AI and Generative AI techniques to enhance data analysis and predictive modeling. Predictive Quality: Ability to apply statistical methods and machine learning algorithms to predict product quality and identify potential issues proactively. Anomaly Detection: Experience in identifying and investigating anomalies in data to uncover potential quality problems. Root Cause Analysis: Expertise in conducting root cause analysis to identify the underlying causes of quality issues. Corrective Action Management: Ability to develop and implement corrective action plans to address quality issues and prevent recurrence. DFMEA, DRBFM, APQP: Familiarity with DFMEA , DRBFM , and APQP methodologies for design and process improvement. Statistical Tools: Proficiency in using various statistical tools for data analysis and quality control. Structured Problem Solving: Ability to apply structured problem-solving techniques to identify and resolve quality issues. Process Optimization: Experience in identifying and implementing process optimization initiatives to improve quality and efficiency. Lean & Six Sigma: Knowledge of Lean and Six Sigma principles for continuous improvement. Quality Tools: Familiarity with various quality tools and techniques for data analysis and problem-solving. Issue Management: Ability to effectively manage and track quality issues to resolution. Warranty Management: Experience in managing warranty claims and analyzing warranty data. Field Quality Analysis: Ability to analyze field quality data to identify trends and patterns. Design Assessment: Ability to conduct design assessments to identify potential quality risks and improve product designs. Design Integrity: Understanding of design integrity principles and their impact on product quality. Design Robustness: Ability to evaluate and improve the design robustness of products. Lessons Learned Deployment: Ability to capture and deploy lessons learned from quality issues to prevent recurrence. Analytical Skills: Strong analytical skills with the ability to interpret data and draw meaningful conclusions. Problem-Solving Skills: Excellent problem-solving skills with the ability to identify and resolve complex quality issues. Data Interpretation Skills: Ability to accurately interpret data and translate it into actionable insights. Communication Skills: Excellent communication skills with the ability to effectively communicate technical information to both technical and non-technical audiences. Stakeholder Management: Ability to build and maintain relationships with key stakeholders . Leadership-Ready Presentation Skills: Ability to deliver compelling and persuasive presentations to senior management. Qualifications: Bachelor’s degree in Electrical Engineering, Electronics Engineering, Automotive Engineering, Data Analytics, Computer Science, or a related engineering discipline. What We Offer Experience Required: 5 - 10 years of relevant experience. Salary:

Quality Data Analyst – Electrical Hardware EngineeringWarranty Analytics | KPI Automation | Design Assessment | AI Adoption

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a skilled and experienced Quality Data Analyst to join our Electrical Hardware Engineering team. This role will focus on Warranty Analytics, KPI Automation, Design Assessment, and the adoption of AI within our quality processes. The ideal candidate will possess a strong analytical background and a passion for leveraging data to drive improvements in product quality and operational efficiency. This is an onsite position. Key Responsibilities The Quality Data Analyst will be responsible for a range of tasks including: Performing Data Analysis to identify trends and patterns in warranty data, product performance, and manufacturing processes. Developing and maintaining KPI Reporting dashboards to track key quality metrics and provide actionable insights to stakeholders. Automating KPI generation and reporting processes to improve efficiency and accuracy. Conducting Root-Cause Analysis of quality issues and collaborating with engineering teams to implement effective Corrective Action Management plans. Utilizing Data Mining techniques to uncover hidden patterns and insights within large datasets. Applying Statistical Analysis methods to evaluate product performance and identify areas for improvement. Leveraging AI-Assisted Analytics and Generative AI to enhance data analysis capabilities and identify potential quality risks. Implementing Process Optimization strategies to streamline quality control processes and improve overall efficiency. Required Skills & Qualifications To be successful in this role, candidates must possess the following skills and qualifications: A Bachelor’s degree in Electrical Engineering, Electronics Engineering, Automotive Engineering, Data Analytics, Computer Science, or a related engineering discipline. 5-10 years of experience in a data analysis role, preferably within the automotive or technology industry. This level of experience indicates a proven ability to independently manage complex data analysis projects and deliver impactful insights. Data Analysis : A strong foundation in data analysis techniques, including data cleaning, transformation, and exploration. Data Visualization : Proficiency in creating compelling and informative data visualizations to communicate insights effectively. Dashboarding : Experience in designing and developing interactive dashboards using tools such as Power BI . KPI Reporting : Ability to define, track, and report on key performance indicators ( KPIs ) to measure quality performance. Data Storytelling : Skill in translating complex data into clear and concise narratives that resonate with stakeholders. Quality Tools : Familiarity with various quality tools and methodologies, such as Lean and Six Sigma . Issue Management : Experience in identifying, tracking, and resolving quality issues in a timely and effective manner. Root-Cause Analysis : Ability to conduct thorough root-cause analyses to identify the underlying causes of quality problems. Corrective Action Management : Experience in developing and implementing corrective action plans to prevent recurrence of quality issues. Process Optimization : Ability to identify and implement process improvements to enhance quality control processes. Power BI : Proficiency in using Power BI to create interactive dashboards and reports. Excel Analytics : Advanced skills in Excel for data analysis and reporting. SQL : Strong proficiency in SQL for querying and manipulating data. Python : Experience using Python for data analysis and automation. Databricks : Familiarity with Databricks for big data processing and analysis. Power Automate : Experience using Power Automate for automating data-related tasks. Warranty Data Analytics : Experience analyzing warranty data to identify trends and patterns. Cost Trend Analysis : Ability to analyze cost trends to identify opportunities for cost savings. KPI Automation : Experience automating KPI generation and reporting processes. Multi-Source Data Integration : Ability to integrate data from multiple sources into a unified view. AI-Assisted Analytics : Experience leveraging AI to enhance data analysis capabilities. Predictive Quality : Ability to use data to predict potential quality issues. Anomaly Detection : Skill in identifying unusual patterns or outliers in data. Generative AI : Familiarity with Generative AI techniques for data analysis and insights. Process Automation : Experience automating manual processes to improve efficiency. Data Mining : Ability to extract valuable insights from large datasets. Statistical Analysis : Proficiency in applying statistical methods to analyze data. Quality Metrics : Understanding of key quality metrics and their application. Data Definitions : Ability to define clear and consistent data definitions. What We Offer We offer a competitive salary of .

Quality Data Analyst – Electrical Hardware Engineer

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a skilled and experienced Quality Data Analyst to join our Electrical Hardware Engineering, Warranty Analytics & Quality Automation team. This role will be instrumental in leveraging data to drive quality improvements, identify trends, and ensure the reliability of our products. The ideal candidate will possess a strong analytical background, a passion for data-driven decision-making, and a commitment to continuous improvement within the automotive and technology industries. Key Responsibilities The Quality Data Analyst will be responsible for a range of tasks related to data analysis, reporting, and process improvement. This includes conducting in-depth analysis of warranty data, identifying cost trends, and developing automated reporting solutions. The role will also involve collaborating with cross-functional teams to implement corrective actions and preventative measures to enhance product quality and reliability. Required Skills & Qualifications To be successful in this role, candidates must possess a combination of technical skills, analytical abilities, and a strong understanding of quality methodologies. Specific requirements include: Analytical Skills: Demonstrated ability to analyze complex data sets, identify patterns, and draw meaningful conclusions. Problem-Solving Skills: Proven ability to approach complex problems systematically, identify root causes, and develop effective solutions. Data Analysis: Proficiency in data analysis techniques, including statistical analysis and data mining. Data Visualization: Ability to create clear and compelling data visualizations to communicate insights effectively. Dashboarding: Experience in designing and developing interactive dashboards to monitor key performance indicators (KPIs). KPI Reporting: Ability to generate regular reports on KPIs and present findings to stakeholders. Data Storytelling: Ability to translate data into a narrative that is easy to understand and actionable. SQL: Strong proficiency in SQL for data extraction, manipulation, and analysis. Python: Experience using Python for data analysis and automation. Databricks: Familiarity with Databricks for large-scale data processing and analytics. Power Automate: Experience with Power Automate for automating data-related tasks and workflows. Warranty Data Analytics: Expertise in analyzing warranty data to identify trends and opportunities for improvement. Cost Trend Analysis: Ability to analyze cost data to identify trends and potential cost savings. KPI Automation: Experience in automating the generation and distribution of KPIs. Multi-Source Data Integration: Ability to integrate data from multiple sources into a unified view. AI-Assisted Analytics: Experience leveraging AI to enhance data analysis and predictive modeling. Predictive Quality: Knowledge of predictive quality techniques to anticipate and prevent quality issues. Anomaly Detection: Ability to identify unusual patterns or outliers in data that may indicate quality problems. Generative AI: Familiarity with Generative AI techniques for data analysis and problem-solving. Issue Management: Experience in tracking and resolving quality issues. Root-Cause Analysis: Proficiency in conducting root-cause analysis to identify the underlying causes of quality problems. Corrective Action Management: Ability to develop and implement effective corrective actions to prevent recurrence of quality issues. DFMEA: Understanding of DFMEA (Design Failure Mode and Effects Analysis) principles. DRBFM: Understanding of DRBFM (Design Review Based on Failure Mode) principles. APQP: Understanding of APQP (Advanced Product Quality Planning) principles. Statistical Tools: Proficiency in using various statistical tools for data analysis and quality improvement. Structured Problem Solving: Ability to apply structured problem-solving methodologies to address quality challenges. Power BI: Proficiency in Power BI for data visualization and reporting. Excel Analytics: Strong Excel skills for data analysis and reporting. Process Optimization: Ability to identify and implement process improvements to enhance quality and efficiency. Six Sigma: Knowledge of Six Sigma methodologies for process improvement. Quality Tools: Familiarity with various quality tools and techniques. Lean: Understanding of Lean principles for waste reduction and process improvement. Education: A Bachelor’s degree in Electrical Engineering, Electronics Engineering, Automotive Engineering, Data Analytics, Computer Science, or a related engineering discipline is required. Experience: The ideal candidate will have 5-10 years of experience in a related field, demonstrating a strong track record of success in data analysis and quality improvement. This level of experience is expected to provide a solid foundation for independent work and leadership within a team. What We Offer Salary:

Artificial Intelligence Senior Associate

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a highly motivated and skilled Artificial Intelligence Senior Associate to join our growing team in India. This role is ideal for a candidate with a strong foundation in data science and a passion for leveraging AI/ML to solve complex business challenges within the Technology industry. Key Responsibilities The Artificial Intelligence Senior Associate will be responsible for a range of tasks related to the development, implementation, and maintenance of AI/ML solutions. This includes collaborating with cross-functional teams to identify opportunities for AI/ML applications, designing and building AI/ML models, and ensuring the scalability and reliability of these models in a production environment. The role requires a proactive approach to problem-solving and a commitment to continuous improvement. Required Skills & Qualifications AI/ML : A deep understanding of artificial intelligence and machine learning principles, including various algorithms and techniques for model building, training, and evaluation. Python : Proficiency in Python programming language for data manipulation, statistical analysis, and AI/ML model development. Google Cloud Platform (GCP) : Experience with GCP services, including Big Query , Dataproc , Data Fusion , and Cloud SQL , for data storage, processing, and analysis. Data/Analytics : Strong analytical skills with the ability to extract meaningful insights from large datasets and communicate findings effectively. Automation : Experience in automating data processing and AI/ML workflows to improve efficiency and reduce errors. Business Analysis : Ability to understand business requirements and translate them into technical specifications for AI/ML solutions. Business Transformation : A grasp of how AI/ML can be leveraged to drive business transformation and create competitive advantage. CI/CD : Familiarity with continuous integration and continuous delivery ( CI/CD ) practices for deploying and managing AI/ML models. ETL : Experience with extract, transform, load ( ETL ) processes for data integration and preparation. Jira : Proficiency in using Jira for project management and issue tracking. Data Flow : Understanding of data flow principles and techniques for designing efficient data pipelines. TERRAFORM : Experience with TERRAFORM for infrastructure as code. Tekton : Knowledge of Tekton for container-native CI/CD. AIRFLOW : Experience with AIRFLOW for orchestrating complex data workflows. Airflow PySpark : Ability to utilize Airflow with PySpark for large-scale data processing. POSTGRES : Familiarity with POSTGRES database. API : Understanding of API design and integration. GCP : Comprehensive knowledge of GCP ecosystem. Financial Reporting : Ability to apply AI/ML techniques to financial data and generate insightful reports. Leadership : Demonstrated leadership potential with the ability to guide and mentor junior team members. Strategic Communication : Excellent communication skills with the ability to present complex technical concepts to both technical and non-technical audiences. Communication Skills : Strong written and verbal communication skills. Analytical Skills : Exceptional analytical and problem-solving skills. Problem-Solving Skills : Ability to identify, analyze, and solve complex problems effectively. GitHub : Proficiency in using GitHub for version control and collaboration. Qualifications : A Bachelor's Degree and a Master's Degree are required. Experience Required : We are seeking candidates with 3-9 years of relevant experience in data science or a related field. This level of experience indicates a strong foundation in AI/ML principles and a proven ability to deliver impactful results. What We Offer Salary :

Power Platform Software Engineer

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a skilled Power Platform Software Engineer to join our IT / Technology team. This role will focus on leveraging the capabilities of the Power Platform to build and maintain robust, efficient, and scalable solutions. The ideal candidate will possess a strong foundation in software development principles and a passion for utilizing innovative technologies to solve complex business challenges. Key Responsibilities The Power Platform Software Engineer will be responsible for the full lifecycle of application development, from initial design and development to testing, deployment, and ongoing support. This includes collaborating with stakeholders to gather requirements, translating those requirements into functional solutions, and ensuring the quality and performance of the developed applications. Required Skills & Qualifications Education: A Bachelor's Degree is required. Experience: 6 years of experience in software development is expected. This level of experience indicates a proficiency in designing, developing, and implementing complex software solutions. Programming Languages: Demonstrated proficiency in Python is essential. Data Visualization & Business Intelligence: Expertise in Power BI for creating insightful reports and dashboards. Data Warehousing & Analytics: Experience with BigQuery for data analysis and querying. Artificial Intelligence: Familiarity with AI concepts and their application in business solutions. Power Platform Development: Strong skills in Power Apps for building custom applications, Power Automate for workflow automation, and Copilot Studio for creating intelligent chatbots. Microsoft Technologies: Proficiency in Microsoft Sharepoint for collaboration and document management, Microsoft Copilot for enhanced productivity, and AI Builder for incorporating AI capabilities into applications. Data Management: Experience with Microsoft Dataverse for data storage and management. API Integration: Ability to work with Microsoft Graph API and REST APIs for integrating with external systems. Cloud Computing: Solid understanding of Azure Services and GCP for cloud-based application deployment and management. Integration Technologies: Experience with Logic Apps and Azure Functions for building integrations and automating tasks. Data Management & Integration: Ability to perform Data Integration and Migration of data. Software Development Best Practices: Strong understanding of Reporting , Analytics , Testing , Quality Assurance , and UAT methodologies. Collaboration & Communication: Excellent Collaboration and Support skills for working effectively with cross-functional teams. Application Lifecycle Management: Experience in App Development , Modernization , and Optimization of existing applications. Workflow Automation: Ability to design and implement Workflow Automation solutions. What We Offer

Software Engineer (3) - Core Engineer 0

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking a highly motivated and skilled Software Engineer to join our core engineering team. This role will be responsible for developing and maintaining core software components, leveraging a variety of technologies to deliver high-quality solutions. The ideal candidate will possess a strong foundation in software development principles and a passion for continuous learning. Key Responsibilities This role will focus on the development and maintenance of core software components, ensuring their reliability, scalability, and performance. Specific responsibilities will be defined based on project needs and evolving business requirements. Required Skills & Qualifications Education: A Bachelor's Degree is required. Programming Languages: Proficiency in Python is essential. Data Analytics & Business Intelligence: Experience with Power BI for data visualization and reporting, and BigQuery for data warehousing and analysis. Artificial Intelligence & Machine Learning: Familiarity with AI concepts and applications, including experience with Microsoft Copilot , Copilot Studio , and AI Builder . Microsoft Power Platform: Strong skills in Power Apps for low-code application development and Power Automate for Workflow Automation . Cloud Computing: Experience with GCP and Azure Services , including Azure Functions and Logic Apps . Data Management: Knowledge of Dataverse for data storage and management. API Integration: Ability to work with REST APIs and Microsoft Graph API for data integration and application connectivity. User Interface & Experience: Understanding of User Experience ( UX ) and UI design principles. Software Development Lifecycle: Experience with Testing , Quality Assurance , and UAT processes to ensure software quality. Collaboration & Communication: Excellent Collaboration and Support skills to work effectively within a team environment. Microsoft Ecosystem: Proficiency with Microsoft Sharepoint . Experience: 6 years of experience are required. This indicates a senior level of experience, with expectations of independent problem-solving, mentorship of junior team members, and contribution to architectural decisions. Work Mode: onsite

MATLAB Application & Data Analytics Engineer – EV

SACHA Engineering•

Chennai

•full time

Skill Set: MATLAB, Simulink, M-scripting, Python, Data Analytics, GCP, Github, BEV, HEV Job Description: - Develop tools using MATLAB, Python for retrieving, processing and aggregating data from a variety of different and internal 3rd party data resources to aid in vehicle optimization. - Develop cutting edge software and analytical solutions to solve complex electrified propulsion system challenges and improve customer experience of advanced electrified vehicles. - Integrate software and analytical tools to support processing and analysis of both simulation and real-world data. - Create and maintain unit tests of core software functionality to ensure robustness across different compute environments. - Create standardized report tools, metrics and visualisations to support different use cases. - Use version control systems (Github) to maintain software traceability and perform documentation of code, data and process. Domain Knowledge: - Strong experience in MATLAB scripting developing applications and processing and analysing a larger set of data for both Windows and Linux (Mandatory). - Knowledge towards MATLAB and Simulink (Mandatory). - Experience in developing applications using Python using data science libraries (Pandas, NumPy, SciPy, etc.) for both Windows and Linux is added advantage. - Experience/knowledge towards GCP. - Working knowledge of HEV/BEV vehicles. - Demonstrated strong written and verbal communication skills. - Excellent organizational skills including attention to detail and multi-tasking skills.