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Mid-level popular title in Hyderabad at a known financial brand with broad mid-level requirements increases competition.
Core data engineering skills are transferable, but finance domain knowledge is preferred, increasing domain sensitivity.
Multiple mandatory technologies plus a 3+ years requirement creates stringent shortlisting filters.
Design and build production-grade ELT/ETL data pipelines using batch and streaming ingestion with modern storage formats like Apache Iceberg and Delta Lake.
Deliver governed, trusted, and self-service data products and support semantic models and feature-ready datasets for AI/ML initiatives.
Ensure data quality controls, governance, compliance, and optimize scalable data pipelines leveraging AI-assisted development tools.
Minimum 3+ years experience in data engineering, building enterprise-scale data platforms.
Bachelor’s degree in Computer Science, Engineering, or related discipline.
Proficiency with AWS, SQL, Python, Apache Spark (PySpark), Snowflake, Lakehouse, Apache Iceberg, Delta Lake, CI/CD, Git, Docker, Kubernetes, and Terraform.
Work Shift Requirement: 2:00 PM - 11:00 PM IST.
Experienced data engineer skilled in cloud-native data architectures and scalable data pipeline development.
Experienced in implementing data governance, quality frameworks, and delivering production-ready data products for business and AI/ML teams.
Capable of collaborating directly with stakeholders and cross-functional teams to translate business needs into technical solutions within regulated environments.