Data Pipelines Jobs

SAP BTP Integration & Build Apps Specialist

SACHA Engineering•

Hyderabad

•full time

Job Summary We are seeking a skilled and experienced SAP BTP Integration & Build Apps Specialist to join our team in a hybrid work mode. This role will be pivotal in designing, building, and maintaining integrations and applications on the SAP Business Technology Platform (BTP) , ensuring alignment with business requirements and adherence to security and compliance standards. Key Responsibilities The SAP BTP Integration & Build Apps Specialist will be responsible for a range of tasks including, but not limited to, the design, development, and implementation of SAP BTP -based solutions. This includes building and maintaining CI/CD pipelines , ensuring application stability , and creating comprehensive technical documentation and operational runbooks . The role also involves collaborating with cross-functional teams to ensure seamless integration with existing S/4HANA systems and adherence to audit and compliance requirements. Required Skills & Qualifications SAP BTP : Demonstrated proficiency in utilizing SAP Business Technology Platform for application development and integration. Cloud Foundry : Strong understanding and practical experience with the Cloud Foundry platform. Destination & Connectivity Services : Expertise in configuring and managing Destination & Connectivity Services for secure and reliable data exchange. XSUAA : Proficiency in utilizing XSUAA for authentication and authorization within SAP BTP environments. Cloud Identity Services (IAS/IPS) : Experience with Cloud Identity Services (IAS/IPS) for managing user identities and access. Cloud Connector : Ability to configure and manage the Cloud Connector for hybrid scenarios. CI/CD pipelines : Experience in designing and implementing CI/CD pipelines for automated build, testing, and deployment. Git : Proficient in using Git for version control and collaborative development. SAP Build Apps : Experience in developing applications using SAP Build Apps , including Logic flows & data modeling and UI/UX configuration . Role-based access configuration : Ability to configure role-based access controls to ensure data security and compliance. Mobile/web deployment : Experience in deploying applications to mobile and web environments. OData services : Understanding of OData services for data integration and exchange. REST APIs : Experience working with REST APIs for application integration. CDS exposure (consumption) : Ability to consume CDS (Core Data Services) for data access. ABAP : Familiarity with ABAP programming for custom development and integration. SAP Integration Suite : Experience with SAP Integration Suite for integration scenarios. OAuth2, SAML : Knowledge of OAuth2 and SAML for secure authentication and authorization. Certificates : Ability to manage and configure Certificates for secure communication. Event Mesh : Understanding of Event Mesh for event-driven integration. Build Apps development standards : Adherence to Build Apps development standards for code quality and maintainability. Application stability : Focus on ensuring application stability and performance. Technical documentation : Ability to create clear and concise technical documentation . Operational runbooks : Experience in developing operational runbooks for incident response and troubleshooting. Audit, Compliance, Security standards : Understanding of audit , compliance , and security standards . Clean-core extensibility concepts : Knowledge of Clean-core extensibility concepts . CAP (Cloud Application Programming Model) : Experience with CAP (Cloud Application Programming Model) . S/4HANA business processes : Understanding of S/4HANA business processes , including FI , MM , and SD . SLA : Ability to meet SLA requirements. Experience Required: The ideal candidate will possess 8-15 years of relevant experience in SAP development and integration, demonstrating a strong track record of delivering high-quality solutions. What We Offer Salary: 30 LPA

Artificial Intelligence Senior Associate

RLE India Private Limited•

Chennai

•Full-time

Artificial Intelligence Senior Associate Job Summary We are seeking a highly motivated and skilled Artificial Intelligence Senior Associate to join our growing team in Chennai. This role offers an exciting opportunity to contribute to cutting-edge AI and ML initiatives within a dynamic Technology environment. Key Responsibilities The Artificial Intelligence Senior Associate will be responsible for a range of tasks related to the development, deployment, and maintenance of AI and ML models and systems. This includes collaborating with cross-functional teams to define project requirements, designing and implementing solutions, and ensuring the quality and reliability of deployed models. Required Skills & Qualifications AI/ML : A strong understanding of artificial intelligence and machine learning principles, including various algorithms, techniques, and their practical applications. GCP : Proficiency in utilizing Google Cloud Platform ( GCP ) for developing and deploying AI and ML solutions. This includes experience with GCP services such as Vertex AI, BigQuery, and Cloud Storage. GenAI : Experience with Generative AI models and techniques, including understanding of large language models and their applications. AI Agents : Familiarity with the principles and implementation of AI Agents , including their design, development, and integration into existing systems. MLOps : Knowledge of MLOps practices and tools for automating and streamlining the machine learning lifecycle, from model development to deployment and monitoring. RESTful APIs : Ability to design and implement RESTful APIs for integrating AI and ML models with other systems and applications. Microservices : Experience with microservices architecture and its application in building scalable and resilient AI and ML systems. Data Pipelines : Ability to design and implement robust and efficient data pipelines for ingesting, transforming, and preparing data for AI and ML models. Model Monitoring : Experience with model monitoring techniques and tools for tracking model performance and identifying potential issues. Model Governance : Understanding of model governance principles and best practices for ensuring the ethical and responsible use of AI and ML models. Serverless : Familiarity with serverless computing concepts and technologies for building scalable and cost-effective AI and ML applications. Containerized : Experience with containerized deployments using technologies like Docker and Kubernetes . Agile : Experience working in an Agile development environment, with a focus on iterative development and continuous improvement. Product Management : Ability to collaborate with product management teams to define requirements and translate them into technical solutions. Reasoning : Strong analytical and reasoning skills for problem-solving and decision-making in complex situations. Tool-use : Ability to effectively utilize various AI and ML tools and technologies. APIs : Understanding of APIs and their role in integrating AI and ML models with other systems. Qualifications : A Bachelor's Degree is required. Experience Required : 3 - 5 years of relevant experience in the field of AI and ML . What We Offer We offer a competitive compensation package.

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. This role will focus on leveraging cutting-edge AI/ML techniques to solve complex business challenges within the IT / Technology industry. Key Responsibilities The Artificial Intelligence Senior Associate will be responsible for a range of tasks related to the development, deployment, and maintenance of AI/ML models and systems. This includes contributing to the full lifecycle of AI projects, from initial conception and design to implementation, testing, and ongoing monitoring. Required Skills & Qualifications AI/ML : A strong understanding of artificial intelligence and machine learning principles, including various algorithms and techniques for data analysis, prediction, and automation. GCP : Proficiency in utilizing Google Cloud Platform (GCP) for developing and deploying AI/ML solutions. This includes familiarity with GCP Services and their integration within a cloud-based environment. GenAI : Experience with Generative AI models and their applications. AI Agents : Knowledge of AI Agents and their implementation. RESTful APIs : Ability to design and integrate with RESTful APIs for seamless data exchange and system interoperability. Microservices : Understanding of Microservices architecture and its application in building scalable and resilient AI systems. MLOps : Experience with MLOps practices to streamline the machine learning lifecycle, including automation, continuous integration, and continuous delivery. Serverless : Familiarity with Serverless computing concepts and their application in building efficient and cost-effective AI solutions. Containerized : Experience with Containerized environments, such as Docker and Kubernetes , for deploying and managing AI applications. Agile : Proven ability to work within an Agile development framework, collaborating effectively with cross-functional teams. Product Management : Understanding of Product Management principles and their application in defining and delivering successful AI -powered products. Reasoning : Ability to apply logical Reasoning to solve complex problems and make informed decisions. Tool-use : Proficiency in utilizing various AI and ML tools and frameworks. APIs : Experience with APIs and their integration. Data Pipelines : Ability to design and implement robust Data Pipelines for efficient data processing and transformation. Model Training : Expertise in Model Training techniques and best practices. Model Deployment : Experience with Model Deployment strategies and tools. Model Versioning : Ability to implement Model Versioning to track and manage different versions of AI models. Model Monitoring : Proficiency in Model Monitoring techniques to ensure the ongoing performance and accuracy of AI models. Model Governance : Understanding of Model Governance principles and their application in ensuring responsible and ethical use of AI . Qualifications : A Bachelor's Degree is required. Experience Required : 3 - 5 years of relevant experience in the field of AI/ML is expected. This level of experience indicates a solid foundation in AI principles and a proven ability to contribute effectively to real-world projects. What We Offer Salary:

Software Engineer (2) - Commodity Engineer 0

RLE India Private Limited•

Chennai

•full time

Job Summary We are seeking two experienced Software Engineers to join our team in Bangalore. This role focuses on the development and maintenance of our Pega platform, with a strong emphasis on Commodity Engineer principles. The ideal candidate will possess a strong foundation in software engineering principles and a passion for building robust and scalable solutions. Key Responsibilities This role requires a high level of proficiency in designing, developing, and implementing solutions within the Pega environment. You will be responsible for the entire software development lifecycle, from requirements gathering to deployment and ongoing support. A key aspect of this role will be leveraging Automation Tools and DevOps Practices to ensure efficient and reliable delivery of high-quality software. Required Skills & Qualifications Education: A Bachelor's Degree is required. Experience: A minimum of 6-8 years of experience in software engineering is expected. This level of experience indicates a proven ability to independently design, develop, and implement complex software solutions, as well as mentor junior team members. Core Technologies: Pega and Pega PRPC Proficiency: Demonstrated expertise in the Pega platform, including Pega Constellation , Ruleset Strategy , Case Architecture , and Integration Architecture . Programming Languages: Strong proficiency in Python , C# , and JavaScript . .NET Development: Experience with .NET Developer , .Net Framework . RESTful Services, JSON, XML, HTTP, API: Ability to design and consume RESTful Services and work with data formats like JSON and XML . Cloud Technologies: Google Cloud Platform: Familiarity with Google Cloud Platform services. Cloud-Native Deployments: Experience with Cloud-Native Deployments , Kubernetes , AKS , and EKS . DevOps & Automation: DevOps Practices: Solid understanding of DevOps Practices , including CI/CD Pipelines and Release Governance . Automation Frameworks: Experience with Automation Frameworks . Pipeline Deployments: Ability to manage Pipeline Deployments and adhere to Merge Governance best practices. Data & Architecture: Data Model: Strong understanding of Data Model concepts. Microservices Architecture: Experience with Microservices Architecture . AI & Machine Learning: AI: Basic understanding of AI principles. GenAI: Exposure to GenAI concepts. Agentic AI: Familiarity with Agentic AI . Domain Knowledge: Banking, Financial Services: Understanding of Banking and Financial Services concepts, including Disputes , Cards , Payments , and Lending . Pega Smart Disputes: Experience with Pega Smart Disputes . Compliance, Regulatory Considerations: Awareness of Compliance and Regulatory Considerations . Other Skills: Analytical Skills: Strong Analytical Skills for problem-solving and data analysis. Problem-Solving Skills: Excellent Problem-Solving Skills to identify and resolve complex technical issues. Communication Skills: Effective Communication Skills to collaborate with cross-functional teams. What We Offer Salary:

Azure Cloud & Data ETL Developer

SACHA Engineering•

Bengaluru

•full time

Job Summary We are seeking a skilled and experienced Azure Cloud & Data ETL Developer to join our dynamic IT / Technology team. This is a hybrid role, offering a blend of remote work and in-office collaboration. The ideal candidate will possess a strong background in data engineering, cloud technologies, and ETL/ELT development, with a focus on the Azure ecosystem. Key Responsibilities The Azure Cloud & Data ETL Developer will be responsible for designing, developing, and maintaining robust and scalable data pipelines and solutions within the Azure cloud environment. This includes data ingestion, transformation, and loading processes, ensuring data quality, and adhering to data governance principles. The role also involves collaborating with cross-functional teams to understand data requirements and deliver effective solutions. Required Skills & Qualifications Azure Data Services: Demonstrated proficiency in utilizing various Azure data services, including Azure Data Factory (ADF) , Azure Databricks , and Azure Synapse Analytics , to build and manage data pipelines. ETL Development: Extensive experience in ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) development, including designing and implementing data integration solutions. Hybrid Data Architectures: A strong understanding of hybrid data architectures , enabling seamless data flow between on-premises and cloud environments. Cloud Migration: Experience in migrating data and applications to the Azure cloud platform. Data Engineering: Solid foundation in Data Engineering principles and practices. Data Modeling: Expertise in data modeling techniques, including the design and implementation of star schemas and snowflake schemas . Data Warehousing Concepts: A thorough understanding of data warehousing concepts and best practices. Programming Languages: Proficiency in Python and PySpark for data manipulation and processing. Data Ingestion & Integration: Experience with data ingestion and data integration processes, ensuring data accuracy and consistency. Data Quality & Governance: Knowledge of data quality and data governance principles and practices. DevOps & CI/CD: Experience with DevOps practices, including CI/CD (Continuous Integration/Continuous Delivery) pipelines, utilizing tools like Azure DevOps and GitHub Actions . Agile Methodology: Familiarity with Agile development methodologies. Performance Tuning & Indexing: Ability to perform performance tuning and indexing to optimize data query performance. Data Validation: Experience in implementing data validation processes to ensure data integrity. Azure Data Lake Storage (ADLS): Experience working with Azure Data Lake Storage (ADLS) . Communication Skills: Excellent communication skills , both written and verbal, to effectively collaborate with stakeholders. Problem-Solving Skills: Strong problem-solving skills to identify and resolve data-related issues. Gemini AI: Familiarity with Gemini AI and its applications in data processing. Experience Required: 6 - 10 years of relevant experience in data engineering and cloud development. This level of seniority requires a proven track record of designing and implementing complex data solutions, leading projects, and mentoring junior team members. What We Offer Salary: 18 LPA