We are looking for an experienced AWS Data Engineer with strong expertise in AWS Data Services, Big Data Technologies, Data Warehousing, ETL Development, Python, Scala, and Data Modeling. The ideal candidate will be responsible for designing, building, and maintaining enterprise-scale data platforms, cloud-native data pipelines, and analytics solutions on AWS.

The role requires hands-on experience with AWS Redshift, Glue, Lambda, Kinesis, Data Warehousing, ETL tools, and Big Data technologies while working closely with business and technical stakeholders.

Key Responsibilities

Data Engineering & Pipeline Development

- Design, build, and operationalize scalable data pipelines on AWS.
- Develop end-to-end data ingestion, transformation, and consumption frameworks.
- Build batch and real-time data processing solutions using AWS native services.
- Design and implement cloud-native ETL and ELT solutions.
- Create reusable data engineering components and frameworks.

AWS Data Platform Development
- Design and develop solutions using:

- AWS Redshift

- AWS Glue

- AWS Lambda

- AWS Kinesis

- Amazon S3

- Amazon EC2
- Build highly available, scalable, and secure data platforms.
- Support data integration and analytics initiatives on AWS.

Data Warehousing & Modeling
- Design and implement enterprise Data Warehouse solutions on AWS.
- Develop and maintain dimensional and relational data models.
- Support data architecture and data governance initiatives.
- Implement best practices for data quality, metadata management, and reporting.

Big Data Engineering
- Develop solutions using:

- Apache Hive

- Scala

- Python

- Big Data frameworks
- Process and optimize large-scale datasets.
- Support both structured and semi-structured data processing requirements.





ETL & Analytics
- Develop ETL workflows using AWS and enterprise ETL tools.
- Work with Informatica and other integration platforms.
- Support data transformation and reporting initiatives.
- Perform ETL validation and testing activities.

Collaboration & Stakeholder Management
- Partner with business users, architects, analysts, and technology teams.
- Participate in requirement gathering, solution design, and implementation activities.
- Manage project-level stakeholder communication and reporting.
- Support Agile delivery and continuous improvement initiatives.

Required Skills

- 7+ years of experience in Data Engineering and Data Warehousing.
- Strong hands-on expertise with:

- AWS Redshift

- AWS Glue

- AWS Lambda

- AWS Kinesis
- Experience designing and implementing enterprise Data Warehouse solutions.
- Strong Data Modeling and Data Analysis experience.

- Robust programming skills in

- Python

- Scala
- Strong SQL development and optimization capabilities.

- Experience with

- ETL Development

- Informatica

- Data Integration Frameworks

- Experience with

- Shell Scripting

- ETL Testing

- Splunk
- Knowledge of Big Data technologies and architecture patterns.

Preferred Skills

- Tableau.
- Power BI.
- Business Analysis.
- Real-Time Data Processing.
- Stakeholder Management.
- Enterprise Data Governance.
- Cloud-Native Analytics Platforms.

Desired Candidate Profile

- Excellent written and verbal communication skills.
- Strong stakeholder management capabilities.
- Ability to work independently and as part of a distributed team.
- Strong analytical and problem-solving mindset.
- Experience working in complex enterprise environments.
- Passion for building scalable cloud data solutions.

📌 Aws Data Engineer (PAN India) (Bengaluru)
🏢 Tata Consultancy Services
📍 Bengaluru