Data Engineer, Financial Crimes, Associate

What you'll do

• Design, develop, and implement robust PySpark-based ETL frameworks with error handling and fault tolerance.
• Perform data enquiry, analysis, and sourcing in Relational and Big Data database environments.
• Translate business requirements into data models and program design specifications.
• Modify ETL programs to implement changes driven by evolving business requirements.
• Respond to queries regarding data access, query design, and performance optimization.
• Troubleshoot data issues and collaborate with upstream teams to identify and resolve root causes.
• Provide Level-3 (L3) production support as needed.
• Use AI-enabled tools to accelerate data mapping, lineage creation, and data profiling.

What we're looking for

• Experience with coding in PySpark, Python, and SQL.
• At least 5 years of financial industry technology experience and knowledge of financial services data.
• Strong knowledge of relational databases and data modeling.
• Strong SQL query-writing skills.
• Strong analytical and troubleshooting skills.
• Good verbal and written communication skills.
• Hands-on experience with Graph Database/Stardog (preferred).
• Experience with coding Autosys job definitions (preferred).
• Experience with Data Modeling tools such as Power Designer (preferred).
• Experience in Linux Shell (preferred).
• Experience in Java Development (preferred).
• Experience and understanding of Data Quality Rules and Implementation (preferred).