Description

You will design and implement scalable data solutions to support complex, large-scale financial data initiatives.

Responsibilities

• Lead the design, development, and optimization of ETL pipelines using PySpark, AWS S3, and Dremio.
• Engineer solutions for data ingestion, transformation, and loading into data lakes and data warehouses.
• Work with structured and unstructured data to support modernization of financial attribution systems.
• Collaborate with BI developers and stakeholders to translate business requirements into technical data flows.
• Monitor, troubleshoot, and resolve performance issues within data workflows while ensuring data quality and governance.

Required Skills

• 5+ years of experience in software engineering with a focus on data engineering and analytics platforms.
• Deep expertise in PySpark and ETL development.
• Hands-on experience with AWS S3 and AWS cloud environments.
• Proven experience in Data Warehousing and Business Intelligence (DW/BI) projects.
• Strong understanding of slowly changing dimensions (SCD), source-of-record (SOR) onboarding, and financial attribution.
• Experience managing data within data lake architectures.
• Ability to work with complex, multi-faceted projects involving booking/referring agreements.

Preferred Skills

• Familiarity with Dremio or similar query acceleration platforms.
• Background in financial services or enterprise-scale data environments.

Key Skills

Education

Any Graduate