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Metro Bengaluru location and desirable data-engineer skills create moderate applicant competition density.
High because capital-markets regulatory context and domain knowledge significantly affect fit despite transferable data skills.
High due to mandatory 8+ years, specific Databricks/PySpark/AWS skillset, and finance domain preferences.
Design, build, and optimize scalable data pipelines and analytical workflows using Databricks, Python, PySpark, and AWS for a Global Capital Markets platform modernization.
Collaborate with Front Office, Product Owners, Risk, Quant Analysts, and Technology teams to deliver production-ready, high-performance data solutions supporting trading systems for FX Cash, Cleared IRS, and new products.
Support migration and modernization initiatives including data platform cloud transformation, define data-quality standards, and participate in Agile delivery and CI/CD processes.
8+ years of experience in Data Engineering, Data Science, or Analytics Engineering roles.
Strong hands-on experience with Databricks on AWS, Spark architecture, and performance tuning.
Advanced skills in Python, PySpark, and AWS services including S3, Glue, Lambda, CloudWatch.
Experience building scalable ETL/ELT pipelines, modern data lake architectures, and developing APIs using FastAPI or similar frameworks.
Experienced data engineer with expertise in capital markets data, especially FX Cash, Cleared IRS, and derivatives products.
Demonstrates ability to work cross-functionally with business stakeholders and technology teams in regulated financial services environments.
Proven track record in large-scale platform modernization, migration programs, and implementing cloud-based distributed data processing solutions.