Pyspark Developer

13 hours ago


Singapore FLARE CONSULTING PTE. LTD. Full time

Job Posting: Spark Developer (Data Modernization Project) About the Role: We are seeking multiple skilled and motivated Spark Developers to join a dynamic data engineering team. You will be a key contributor to a strategic, large-scale data modernization initiative for a leading global financial institution. This project involves the refactoring, upgrading, and deployment of a significant portfolio of PySpark scripts to modernize a critical data platform.This is a fantastic opportunity to work on a high-impact project, enhance your skills with the latest Spark technologies, and gain invaluable experience in the financial services domain.Key Responsibilities: Refactor and upgrade legacy PySpark scripts to be modular, reusable, and compliant with Spark 3.3+ and Python 3.10+. Optimize Spark jobs for high performance using techniques like broadcast joins, effective partitioning, and predicate pushdown. Replace deprecated APIs (e.g., RDDs, legacy UDFs) with optimized DataFrame and Pandas UDF implementations. Implement robust code with structured logging, comprehensive error handling, and alerting mechanisms. Ensure data quality and integrity through schema enforcement, consistent data typing, and correct SCD (Slowly Changing Dimensions) logic. Collaborate within an Agile team, participating in code reviews, sprint planning, and daily stand-ups. Support the integration of code into CI/CD pipelines and contribute to automated testing frameworks. Qualifications and Experience: Education: Bachelor's or Master's degree in Software Engineering, IT, Computer Science, or a related field. Experience: 3 to 5 years of hands-on experience in PySpark development. Mandatory Technical Skills: PySpark Development: 3-5 years of proven experience in refactoring and developing efficient PySpark scripts using DataFrame APIs. Spark Optimization: 2-3 years of practical experience in performance tuning (e.g., broadcast joins, partitioning strategies, predicate pushdown). PySpark Migration: Hands-on experience with PySpark migration or modernization projects. Banking & Financial Data Models: Understanding of financial data concepts, including SCD logic, surrogate keys, and schema evolution. Good-to-Have Skills: Testing Frameworks (e.g., Pytest, Great Expectations). Data Governance & Compliance (e.g., PII/PHI handling, data lineage). Operational Readiness (e.g., backfill support, idempotent writes).


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