Lead Engineer

Mumbai
India
Full time
Job Information

Qualification: Graduate/Postgraduate in Computer Science, IT, or related field                         

Location: Mumbai       Exp: 3-5Years        

+ What are we looking for?  
We are looking for an experienced Data Engineer to design, develop, and maintain scalable data pipelines and data platforms supporting Analytics, AI/ML, and Business Intelligence use cases.The candidate will work closely with Data Scientists, AI Engineers, Analytics teams, SAP teams, and business stakeholders to build reliable, secure, and high-performance data solutions using AWS Cloud and SAP S/4HANA. 


Key Responsibilities 
• Design and develop scalable ETL/ELT pipelines for structured and unstructured data. 
• Build data ingestion and transformation pipelines using Python, SQL, and AWS Cloud services. 
• Develop data integration solutions between SAP S/4HANA and AWS Cloud. 
• Work with AWS services such as Amazon S3, AWS Glue, AWS Lambda, Amazon Athena, Amazon CloudWatch, and IAM. 
• Implement scalable data storage and processing architectures on AWS. 
• Perform data cleansing, transformation, validation, reconciliation, and data-quality checks. 
• Design and implement incremental data loading, CDC, watermarking, and SCD Type 1/Type 2 processes. 
• Optimize data pipelines for performance, scalability, reliability, and cloud cost efficiency. 
• Implement data governance, metadata management, data lineage, security, and access controls. 
• Develop monitoring and alerting mechanisms for production data pipelines. 
• Troubleshoot pipeline failures, data-quality issues, performance bottlenecks, and production incidents. 
• Implement CI/CD practices for data engineering workloads using Git, GitHub, and DevOps tools. 
• Collaborate with Data Scientists and AI/ML Engineers to prepare high-quality datasets and feature pipelines. 
• Support integration of GenAI, RAG, and Agentic AI solutions with enterprise data where required. 
• Document technical architecture, data flows, pipeline logic, data mappings, and operational procedures. 


Required Technical Skills / Programming 
• Strong Python 
• Strong SQL 
• Shell/Bash scripting Data Engineering 
• ETL/ELT 
• Data ingestion and integration 
• Data pipelines 
• Data warehousing 
• Data modelling 
• Data quality and validation 
• Incremental loading / CDC 
• Watermark-based processing 
• SCD Type 1 & Type 2 
• Batch and near-real-time data processing AWS Cloud Strong hands-on experience with: 
• Amazon S3 
• AWS Glue 
• AWS Lambda 
• Amazon Athena 
• Amazon CloudWatch 
• AWS IAM 
• AWS Step Functions / workflow orchestration 
• AWS Event Bridge 
• AWS Secrets Manager 
• AWS CI/CD services  SAP S/4HANA 
• Strong understanding of SAP S/4HANA data structures and business processes. 
• Experience extracting/integrating data from SAP S/4HANA into AWS. 
• Experience with OData, APIs, CDS Views, IDocs, or other relevant SAP interfaces. 
• Understanding of SAP master and transactional data. 
• Ability to work with SAP functional and technical teams for data integration requirements. 
• Experience handling SAP data quality, reconciliation, and incremental extraction. 


AI/ML Data Engineering Exposure 
• The candidate should be able to support modern AI/ML workloads by:Preparing high quality datasets for ML models. 
• Building data pipelines for AI/ML applications. 
• Processing structured and unstructured enterprise data. 
• Supporting RAG pipelines and embedding-generation workflows. 
• Providing governed enterprise data to AI agents and LLM applications. 
• Implementing data validation and monitoring for AI applications. 
• Supporting integration between AWS data platforms and AI/ML solutions. 


Preferred Skills 
• AWS Step Functions / workflow orchestration 
• REST API integration 
• SAP APIs / OData / CDS Views 
• SAP S/4HANA integration 
• Data Catalog and metadata management 
• Data governance and security 
• Docker, CI/CD 
• Git / GitHub / DevOps, Infrastructure as Code 
• Experience supporting AI/ML data pipelines 
• Experience with RAG, embeddings, vector databases, or Agentic AI data workflows 
• Experience in enterprise data migration and integration projects 

Key Competencies 
• Strong problem-solving and analytical skills. 
• Strong understanding of AWS data engineering architecture. 
• Good understanding of SAP S/4HANA data and integration. 
• Ability to troubleshoot production issues independently. 
• Strong focus on data quality, reliability, and security. 
• Understanding of data governance and access controls. 
• Good communication and stakeholder-management skills. 
• Ability to work in an Agile/Scrum environment. 
• Ability to convert business requirements into scalable technical solutions. 


Qualification 
• Bachelor's/Master's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field. 
• 4+ years of relevant Data Engineering experience preferred. 
• Hands-on experience with AWS Cloud and SAP S/4HANA integration is strongly preferred. 


Success Measures 
The Data Engineer will be evaluated on: 
• Reliability and scalability of data pipelines. 
• Data quality and completeness. 
• Successful integration of SAP S/4HANA with AWS. 
• Pipeline performance and optimization. 
• Reduction in processing time and cloud infrastructure cost. 
• Timely resolution of production issues. 
• Reusability and maintainability of data engineering components. 
• Strong data governance and security. 
• Enablement of Analytics, AI/ML, and Business Intelligence use cases.                                                   

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Consultant
Reema Baksi
Reema Baksi
Managing Partner
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