We are seeking a highly skilled 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, developing, and operationalizing enterprise-scale data platforms and analytics solutions on AWS Cloud.

The role requires hands-on experience in building scalable data pipelines, implementing cloud-native data engineering solutions, and supporting modern data warehouse and analytics architectures.

Key Responsibilities

Data Engineering & Pipeline Development

- Design, build, and operationalize enterprise data pipelines on AWS.
- Develop scalable ETL/ELT solutions for batch and real-time data processing.
- Design and implement data ingestion, transformation, and curation frameworks.
- Build end-to-end pipelines from data ingestion to data consumption within big data environments.
- Develop reusable data engineering components and automation frameworks.

AWS Data Platform Development

- Design and develop solutions using AWS services including:

- Amazon Redshift
- AWS Glue
- AWS Lambda
- Amazon Kinesis
- Amazon S3
- Amazon EC2

- Build cloud-native analytics and data integration solutions.

- Support modernization and migration initiatives to AWS cloud data platforms.

Data Warehousing & Modeling

- Design and implement enterprise Data Warehouse solutions on AWS.
- Develop dimensional and relational data models.
- Optimize data structures for reporting, analytics, and business intelligence requirements.
- Support data governance and metadata management activities.

Big Data Engineering

- Develop and optimize solutions using:

- Scala
- Apache Hive
- Python
- Big Data Technologies

- Process and manage large-scale datasets with high performance and scalability.





- Support structured and semi-structured data processing workloads.

ETL & Analytics

- Develop ETL workflows using AWS native services and ETL tools.
- Work with Informatica and other integration platforms.
- Perform ETL testing and data validation.
- Support reporting and analytics initiatives.

Collaboration & Stakeholder Management

- Collaborate with business stakeholders, architects, and development teams.
- Participate in requirement gathering and solution design discussions.
- Support stakeholder management at project level.
- Ensure delivery of scalable, reliable, and business-focused data solutions.

Required Skills

- 6+ years of experience in Data Engineering and Data Warehousing.

- Minimum 3+ years of hands-on experience with AWS Cloud Services.

- Strong expertise in:

- AWS Redshift
- AWS Glue
- AWS Lambda
- AWS Kinesis

- Strong Data Warehousing experience on AWS.

- Experience designing and implementing scalable data pipelines.

- Strong Data Modeling and Data Analysis experience.

- Strong programming skills in:

- Python
- Scala

- Experience with:

- Apache Hive
- ETL Development
- Informatica

- Strong SQL and database development skills.

- Experience with:

- Shell Scripting
- ETL Testing
- Splunk

Preferred Skills

- Tableau.
- Power BI.
- Business Analysis.
- Real-Time Data Processing.
- AWS Analytics Services.
- Stakeholder Management.
- Enterprise Reporting Solutions.

Desired Candidate Profile

- Strong analytical and problem-solving skills.
- Excellent verbal and written communication abilities.
- Experience working with large enterprise data platforms.
- Solid customer and stakeholder management skills.
- Ability to work independently and collaboratively within Agile teams.
- Passion for cloud data engineering and analytics.

📌 AWS Data Engineer (Gurugram)
🏢 Tata Consultancy Services
📍 Gurugram