Principal / Associate Director Data Management Engineering

S&P Global Market Intelligence; Dadri; On-site; INR 3,500,000 - 5,500,000; Full time

Job summary

S&P Global Market Intelligence seeks a Principal/Associate Director for Data Management Engineering to modernize data workflows, implement NeoXam, and advance Databricks adoption, ensuring data quality, scalability, and reliable delivery for index operations.

The role partners with cross-functional teams globally, focusing on ownership, automation, and continuous improvement in a near 24x5 environment. Strong SQL, Python, and data platform expertise are essential.

Qualifications

• Strong SQL Server and T-SQL expertise for data modeling and large-scale processing.
• Python development experience for data processing, APIs, ETL pipelines, and Git workflows.
• Experience with financial data mastering and enterprise data platforms (e.g., NeoXam, Markit EDM).
• Exposure to Databricks/Lakehouse, Jenkins, AWS, scripting, and workflow schedulers preferred.
• Ability to own medium-to-large data management initiatives and work with global teams.

Responsibilities

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

Skills

SQL Server

T-SQL

Python

Databricks

NeoXam

Markit EDM

GitHub

Jenkins

AWS

Tools

NeoXam

Markit EDM

Databricks

GitHub

Jenkins

AWS

Job description

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.