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Tier-1 bank, mid-level data-engineering role in Mumbai with broad AWS/Python/Spark requirements increases applicant density.
Core data-engineering skills (Python, SQL, Spark, AWS) are broadly transferable across industries despite finance preference.
Explicit 3+ years and multiple mandatory skills (SQL, Python, AWS, Airflow, Spark) create strict filtering.
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Design and implement scalable, high-performance cloud-based data solutions to support quantitative research including back testing, simulations, and advanced analytics.
Develop, schedule, monitor, and provide L2 support for ETL/ELT pipelines and data system performance in AWS cloud environments.
Collaborate with technical and quantitative research teams to continuously improve data systems and automate platform scalability, leveraging AI-assisted development tools for code quality and efficiency.
Bachelor's degree in information systems, IT, computer science, or similar fields.
3+ years of applied experience in software engineering, including strong software development lifecycle knowledge and Agile Scrum methodology.
Proficiency in SQL (preferably PostgreSQL), Python (including Pandas/Polars, Numpy, OOP concepts), and AWS cloud technologies such as RDS, S3, Lambda, Secrets Manager.
Experience with ETL/ELT processes, database architecture and performance tuning, orchestration tools like Airflow, data lakes (Iceberg/Delta Table), Spark/EMR, and CI/CD tools for application and database development.
Experienced in building and supporting cloud-based data platforms in a financial or quantitative research environment involving complex data and algorithms.
Skilled in applying AI-assisted software development tools responsibly and effectively within enterprise environments, ensuring security and quality standards.
Capable of translating quantitative research requirements into robust data engineering solutions, with strong communication skills and attention to detail.