Principal / Associate Director Data Management Engineering

Job Summary

Grade Level (for internal use): 12

The Role: Principal / Associate Director - Data Management Engineering

The Team: The Data Management Engineering team supports critical index data workflows across mastering, ingestion, validation, transformation, and distribution. The team partners globally with Business, Index Operations, QA, Architecture, DevOps, and Infrastructure and values technical ownership, data quality, collaboration, automation, and dependable delivery in a near 24x5 operating environment.

The Impact: This role will help modernize SPDJI's data management ecosystem through the implementation of NeoXam and broader adoption of Databricks, while maintaining the resilience of existing enterprise data management platforms. The successful candidate will strengthen the quality, scalability, and operational reliability of financial data workflows that support Index Operations and ultimately contribute to accurate and timely index products for global markets.

Responsibilities

• Lead and support the implementation and onboarding of NeoXam for enterprise data management use cases.
• Design and develop scalable data ingestion, mastering, validation, transformation, and distribution solutions.
• Translate business and operational requirements into effective technical solutions in partnership with Business, Operations, QA, and Architecture.
• Support Databricks-based archival, transformation, and large-scale data processing initiatives.
• Improve data quality, performance, automation, CI/CD, environment management, and operational efficiency.
• Provide production support for critical financial data workflows and maintain clear technical and operational documentation.

Requirements

• Strong SQL Server and T-SQL expertise, including data modeling, database performance optimization, and large-scale data processing.
• Python development experience for data processing and automation, with exposure to APIs, ETL/data pipelines, and Git/GitHub workflows.
• Experience with financial data mastering, transformation, validation, reconciliation, and enterprise data management platforms such as NeoXam, Markit EDM, or similar.
• Experience with Databricks or Lakehouse platforms; exposure to Jenkins, AWS, scripting, workflow schedulers, and environment automation is preferred.
• Demonstrated ability to independently own medium-to-large data management initiatives and solve complex technical problems.
• Strong collaboration and stakeholder-management skills across globally distributed teams.
• Clear written and verbal communication, with a disciplined approach to documentation and operational readiness.
• Interest in both data engineering and operational automation, with a focus on quality, scalability, and continuous improvement.