AWS Data Engineer

Job description

TCS Walk-in at Kolkata- Ecospace Date- 25-Jul-26 JD

Key Responsibilities

Design, develop, and maintain scalable ETL/ELT pipelines using AWS services such as Glue, Lambda, EMR, Step Functions, Kinesis, and Data Pipeline. Build and optimize data models for analytics and reporting using Redshift, Athena, and other data warehouse/lakehouse technologies. Implement and manage data lakes on S3 with appropriate partitioning, security, and governance. Collaborate with data scientists, analysts, and business teams to understand requirements and deliver robust data solutions.

Develop CI/CD pipelines for data workflows using CodePipeline, CodeBuild, or similar tools. Optimize data processing costs, performance, and storage using AWS best practices. Ensure data quality, lineage, and metadata management using Glue Data Catalog or other tools. Monitor, troubleshoot, and improve existing data workflows and cloud infrastructure. Implement IAM-based security policies, encryption, and compliance standards.

Work with DevOps and platform engineering teams to build scalable, secure environments.

Required Skills & Qualifications

Bachelor’s degree in Computer Science, Engineering, or related field. Strong experience with AWS services used for data engineering (Glue, S3, Lambda, EMR, Redshift, Athena, Kinesis). Proficiency in Python and SQL. Hands-on experience with distributed data processing frameworks (Spark, PySpark, Hadoop). Experience building data lakes, data warehouses, and lakehouse architectures. Strong understanding of ETL/ELT design patterns and data modeling (Star/Snowflake).

Knowledge of CI/CD, infrastructure-as-code (Terraform/CloudFormation), and Git. Familiarity with data governance, security, and compliance frameworks. Strong problem‑solving, communication, and collaboration skills.

Qualifications

BACHELOR OF ENGINEERING