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Strong Tier-1 bank, metro location, and broad senior data stack requirements drive high competition.
Security-focused banking context increases domain specificity though core data engineering skills remain somewhat transferable.
Explicit 8–12 years plus mandatory AWS, PySpark, Python, Terraform and security controls makes shortlisting highly strict.
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Own the setup and maintenance of the Group Security Data Platform for ingesting and managing security telemetry and data products.
Design, build, and maintain scalable batch and real-time data pipelines supporting AI/ML and security use cases using AWS cloud services.
Lead end-to-end data engineering lifecycle including requirement gathering, data modeling, development, testing, deployment, and DevSecOps support with focus on data quality, security, and observability.
8-12 years of experience as a Data Engineer in data-intensive environments.
Proficient with AWS services including EC2, S3, Lambda, Athena, Kinesis, Redshift, Glue, EMR, DynamoDB, IAM, and others.
Mandatory strong skills in Python for framework development and experience with big data processing using PySpark/Spark and performance optimization.
Bachelor's or Master's degree in Engineering (Computer Science, IT, or relevant).
Experienced in building and managing complex cloud-based data engineering solutions in a security context, particularly within AWS ecosystem.
Capable of delivering scalable automation frameworks and handling medium to complex engineering initiatives with technical ownership and strategic input.
Skilled in integrating data pipelines with AI/ML and security tooling platforms, applying encryption and data security best practices effectively.