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Tier-1 brand, metro location, mid-level role, and broad in-demand tech stack increases competition.
Core skills (Python, SQL, Spark, AWS) are highly transferable across industries.
Explicit 2+ years and multiple mandatory AWS, Python, Big Data, SQL, and UNIX requirements raise filter strictness.
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Develop, enhance, and test ETL pipelines and interfaces within an agile software engineering team.
Handle DevOps tasks including CICD, code scanning, performance testing, and test coverage.
Transform ETL logic to AWS and Hadoop platforms, innovate data management solutions, and enforce data asset quality standards.
Formal training or certification in software engineering concepts with 2+ years of applied experience.
Proven experience with AWS services (Athena, Redshift, Glue, Aurora, RDS, S3, Lambda, EC2) and Big Data technologies (Hadoop, Spark Architecture, Spark SQL, Kafka).
Strong Python programming skills and SQL query writing experience.
Hands-on experience with UNIX shell scripting and cloud platforms including AWS and DBx.
Experienced in managing complex data transformations and real-time streaming data in Big Data environments.
Familiar with enterprise-authorized AI-assisted software development tools and responsible AI practices.
Comfortable working within agile teams using DevOps tools, with strong analytical skills and attention to detail.