About the Role:

Grade Level (for internal use):

The Team:

The Director of Data Integration & Workflows leads the team that serves as the backbone of enablement at S&P Dow Jones Indices (SPDJI), responsible for building, templating, and standardizing the data pipelines and workflow patterns that power our index and analytical solutions. Reporting to the Director of Data AI & Enablement, this role is critical to the Data Platform enablement strategy, accelerating delivery, reducing production risk, and ensuring that every pipeline and workflow is scalable, observable, and maintainable.

Responsibilities and Impact:

Strategic Leadership & Technical Vision

• Define and drive the data automation and transformation strategy for the Data Integration & Workflows group, setting standards and approaches for building production-ready pipelines and workflow automation across value streams
• Establish reference architectures and engineering standards for ETL/ELT, orchestration, error handling, observability, and performance/cost optimization with clear "definition of done" criteria for production readiness
• Collaborate with the PPD Group to build sustainable, transformational enhancements to the data platform and associated tools
• Foster a culture of technical excellence, craftsmanship, reusable component development, and continuous improvement in automation maturity
• Contribute to the broader Data AI & Enablement strategy, ensuring Data Integration & Workflows capabilities align with organizational strategic goals

Delivery Through Enablement

• Lead delivery through enablement by assessing SME technical capability and selecting the right engagement model
• Partner with value stream SMEs to co-develop and review pipelines, adapting support based on SME technical capability and fostering their growth
• Oversee the design and implementation of robust, reusable data integration and workflow patterns for both batch and streaming use cases
• Partner with PPD on feasibility and planning, providing realistic estimates, identifying dependencies, and shaping technical scope to ensure delivery commitments are achievable and measurable
• Develop and implement training programs to enhance the technical proficiency of value stream SMEs in data engineering practices

Quality Assurance & Production Readiness

• Run the code review and quality gate process for SME-built pipelines, ensuring consistency in maintainability, testing, logging, data validation, and documentation prior to IT handover
• Ensure all solutions are production-ready with comprehensive documentation, testing, error handling, and operational monitoring
• Coordinate seamless IT handover and production gateway readiness, ensuring complete deployment packages (runbooks, architecture notes, testing evidence, monitoring/alerting expectations)
• Partner with IT during QA to resolve issues quickly and ensure solutions meet enterprise standards for quality, security, and supportability
• Implement and maintain governance frameworks specific to data integration, ensuring compliance with organizational policies and industry standards

Operational Excellence

• Provide L3 support for production business-logic issues (in collaboration with value stream SMEs), driving root-cause analysis and permanent fixes for recurring pipeline failures or data breaks
• Ensure implementation of strong data reliability controls including validation rules, reconciliation checks, anomaly detection, and completeness/timeliness controls that protect downstream index processes
• Drive performance and cost optimization through appropriate partitioning, caching, incremental processing patterns, and compute usage tuning—balancing speed, stability, and platform spend
• Establish and monitor operational metrics to track solution delivery timeliness, pipeline reliability, and platform performance

Team Development & Collaboration

• Lead, mentor, and develop a high-performing team of Data Integration Leads and Experts
• Build data engineering capability across the organization through structured mentorship, knowledge sharing, and hands-on coaching
• Collaborate effectively with the other pillars within Data AI & Enablement (AI Solutions and Data Governance) to ensure cohesive platform enablement
• Foster strong partnerships with PPD teams, IT, Data Value Streams, and Data Services & Strategy to align technical enablement efforts with business priorities

Shared Accountabilities

• With PPD: Collaborate on prioritization and alignment of data integration efforts with business requirements and strategic g