Senior AWS Data Engineer

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Senior AWS Data Engineer

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Job Info

• Job Identification16667
• Posting Date07/04/2026, 01:00 AM
• Job RoleData engineer-Engineering
• Experience (In Years)6-9
• Job LocationIndia

Job Description

Manage data engineering projects, ensuring alignment with business objectives. Provide strategic guidance on data engineering best practices. Oversee a team of data engineers. Ensure continuous improvement of data processes.

Responsibilities

Key Responsibilities

• Design, build, and maintain efficient, reusable, and reliable architecture and code for data pipelines and data applications on AWS.

• Build robust data ingestion pipelines (from on-prem to AWS and within AWS) using AWS services such as Glue, Redshift, S3, Lambda, EMR/Spark, Kinesis, and SQS.

• Develop and manage ETL/ELT processes to collect, process, and store data from multiple sources, ensuring data quality, integrity, and security.

• Architect and implement end-to-end data solutions (ingestion, storage, integration, processing, access) on AWS, with a focus on data lakes and data warehouses.

• Participate in the architecture and system design discussions for high-scale data engineering projects.

• Independently perform hands-on development, unit testing, and participate in code reviews to ensure adherence to best practices.

• Implement serverless applications using AWS Lambda, API Gateway, Step Functions, and other AWS technologies.

• Migrate data from traditional relational databases, file systems, and APIs to AWS-based data lakes (S3), RDS, Aurora, and Redshift.

• Implement high-velocity streaming solutions using Amazon Kinesis, SQS, and Kafka (preferred).

• Architect and implement CI/CD strategies for enterprise data platforms.

• Collaborate with product, operations, QA, and cross-functional teams throughout the software development cycle.

• Stay abreast of new technology developments, implement POCs for new tools/technologies, and onboard them for real-world use cases.

• Identify and resolve performance issues and continuously optimize for cost, reliability, and scalability.

Qualifications

Required Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, MIS, or equivalent combination of education and experience.

• 5+ years of experience implementing and supporting data lakes, data warehouses, and data applications on AWS for large enterprises.

• Strong programming experience with Python, Shell scripting, and SQL.

• Solid experience with AWS services: CloudFormation, S3, Athena, Glue, EMR/Spark, RDS, Redshift, DynamoDB, Lambda, Step Functions, IAM, KMS, Secrets Manager.

• Experience in serverless application development and data pipeline orchestration.

• Experience in system analysis, design, development, and implementation of data ingestion pipelines in AWS.

• Knowledge of ETL/ELT, data modeling, and big data technologies.

• Familiarity with data warehousing concepts and cloud-based architecture.

• Strong problem-solving skills and attention to detail.

• Excellent communication and teamwork abilities.

Required Skills

• AWS Cloud Services
• Data Engineering
• ETL
• Pyspark
• Python
• SQL
• Working under Pressure

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