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Mid-level, popular Data Engineer role in Chennai with broad AWS and big-data requirements increases applicant competition.
Core data engineering skills (AWS, Spark, Python) are highly transferable across industries.
Multiple explicit AWS, big-data, and DevOps requirements plus minimum 3+ years make screening stringent.
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Build and maintain scalable ETL/ELT data pipelines using AWS services including Glue, Lambda, and Step Functions.
Manage large structured and unstructured data repositories on AWS (S3, Redshift, DynamoDB, etc.), ensuring data partitioning, indexing, security, and governance.
Optimize performance of data workflows and support data integration from multiple sources with real-time and batch streaming solutions.
3+ years of professional experience in data engineering or software engineering with a strong data focus.
Proven experience designing and delivering complex, production-grade data pipelines using AWS big data tools and programming languages like Python, SQL, and Scala.
Bachelor’s degree (Engineering/Computer Science preferred) or equivalent experience.
Hands-on experience with AWS services (S3, Glue, Redshift, Athena, Lambda, Kinesis), big data tools (Spark, Databricks, Hadoop, Kafka), DevOps practices (Git, CI/CD, CloudFormation/Terraform), and strong data security and governance skills.
Experienced in Agile, cross-functional teams working closely with product, analytics, and data science stakeholders to translate business needs into data solutions.
Comfortable managing end-to-end AWS data infrastructure including provisioning, automation, and monitoring using CloudWatch and CloudTrail.
Skilled in building robust, secure, and scalable data platforms with an emphasis on performance tuning, security compliance, and problem resolution.