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Tier-1 brand, metro location, mid-level generalist data role with broad required skills increases competition.
Technical data engineering skills are transferable across industries, moderately influenced by financial-domain context.
Explicit 5–8 year requirement and many mandatory AWS, PySpark, SQL, and ETL skills make filters strict.
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Build and maintain scalable ETL data pipelines and database systems to support analytics and business intelligence.
Lead all phases of solution development including designing, coding, testing, and deploying data engineering solutions on cloud platforms.
Collaborate with internal clients to translate business requirements into technical specifications, ensuring data quality and system reliability.
5+ years relevant experience including at least 2 years in designing and maintaining data pipelines and ETL processes.
Bachelor’s or Master’s degree in Computer Science, IT, or related field (e.g., B.E., B.Tech., BCA, MCA).
Proficiency in SQL, Python, AWS cloud technologies (including CloudFront, S3, ECS, Lambda, Glue, Athena), and data engineering tools.
Location: Hyderabad, Telangana, India; only qualified external applicants considered.
Experienced data engineer comfortable with event-driven architecture and DevOps practices including Git and continuous delivery pipelines.
Skilled in building reliable, scalable data solutions with a quality-first mindset and ability to use AI-assisted engineering tools effectively.
Able to work collaboratively in agile teams with strong communication skills bridging technical and non-technical stakeholders.