Aws Data Engineer

Tata Consultancy Services; India; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Tata Consultancy Services is seeking an experienced AWS Data Engineer to design, build, and optimize scalable data pipelines and analytics solutions on AWS. The role requires strong expertise in cloud-native data services, big data processing, and end-to-end data engineering practices.

Responsibilities include designing and implementing ETL/ELT pipelines, building data models for analytics, managing data lakes on S3, and collaborating with data scientists and business teams to deliver robust

Qualifications

• Bachelor's degree in CS, Engineering or related field.
• Strong experience with AWS data engineering services (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.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT pipelines using AWS services.
• Build and optimize data models for analytics and reporting.
• Implement and manage data lakes on S3 with partitioning, security, and governance.
• Collaborate with data scientists, analysts, and business teams to 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.

Skills

Python

SQL

Spark/PySpark

Hadoop

ETL/ELT

Data modeling

CI/CD

Terraform/CloudFormation

Git

Security/compliance

Education

Bachelor's degree in Computer Science, Engineering or related field

Tools

Glue

S3

Lambda

EMR

Redshift

Athena

Kinesis

Data Catalog

Terraform/CloudFormation

Git

Job description

Job Description:

Title: AWS Data Engineer

Overview

We are seeking an experienced AWS Data Engineer to design, build, and optimize scalable data pipelines and analytics solutions on AWS. The ideal candidate has strong expertise in cloud-native data services, big data processing, and endtoend data engineering practices.

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

• Bachelors 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 problemsolving, communication, and collaboration skills.

Preferred Qualifications

• AWS Certified Data Analytics Specialty or AWS Solutions Architect Certification.
• Experience with streaming data pipelines (Kinesis, Kafka, MSK).
• Exposure to containerization (Docker, ECS, EKS).
• Knowledge of machine-learning data preparation workflows.

Job Type

Full-time