Data Engineer

Talent Hired-the Job Store; Mumbai; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Talent Hired-the Job Store in Mumbai seeks a Data Engineer with 4-7 years of hands-on experience to design, build, and maintain scalable data pipelines supporting Analytics, AI/ML, and BI use cases.

The ideal candidate will work with AWS Cloud and SAP S/4HANA, collaborate with data scientists and analytics teams, and implement robust data governance, security, and performance optimizations.

Qualifications

• Bachelor’s or Master’s degree in a related field.
• 4+ years of data engineering experience.
• Hands-on AWS Cloud and SAP S/4HANA integration.

Responsibilities

• Design and develop scalable ETL/ELT pipelines for structured and unstructured data.
• Build data ingestion and transformation pipelines using Python, SQL, and AWS services.
• Develop data integration between SAP S/4HANA and AWS Cloud.
• Implement data governance, security, and access controls.
• Collaborate with Data Scientists and AI/ML Engineers for data readiness.
• Implement CI/CD for data engineering workloads.

Skills

Python

SQL

Shell scripting

ETL/ELT

Data pipelines

Data ingestion

Data warehousing

Data modelling

Data quality

Education

Bachelor’s/Master’s degree

Tools

AWS Cloud

SAP S/4HANA

SAP APIs

Job description

Role:- Data Engineer (4-7 years)

Location:- Mumbai

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.

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.

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.