Director, Data Integration & Workflows

S&P Global

Quick summary

Work type: On-site
Location: New York, NY
Salary: $149,031–$228,996 / yr
Posted: 24 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $181k

This role $189k

$127k most similar roles pay here $240k

This role pays more than 52% of similar roles. Most pay $139,500–$222,500 — the shaded band above. At the midpoint, this role pays about $189k versus about $181k for comparable roles.

Based on 240 similar postings.

Employer

About S&P Global

S&P Global delivers Essential Intelligence® that shapes decision making. We provide the world’s leading organizations with the right data, connected technologies and expertise they need to move ahead.

S&P Global currently has 19 open roles on FindRole.

Listed pay typically runs $149,031–$226,998 across 14 roles with salary data.

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View all roles at S&P Global

At a glance

TL;DR · Director, Data Integration & Workflows

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The Director of Data Integration & Workflows leads the enablement strategy at S&P Dow Jones Indices, overseeing a team responsible for building scalable and maintainable data pipelines and workflow patterns. This role involves defining technical standards for ETL/ELT processes, orchestration frameworks, and observability tools, while collaborating with product development teams to enhance the data platform. Key responsibilities include mentoring a high-performing team, developing training programs, ensuring production readiness through rigorous quality gates, and fostering cross-functional partnerships. The ideal candidate has extensive experience in data engineering, leadership roles, and expertise in cloud infrastructure, ETL/ELT design patterns, and modern data platforms like AWS or Azure, along with proficiency in Python, SQL, Scala, and knowledge of DevOps practices.

Skills

AWS Azure GCP ETL/ELT Kubernetes Docker Python SQL Scala CI/CD Terraform Prometheus Grafana DevOps Data质量管理框架监控和警报系统数据治理原则合规框架

What you'll do

Define and drive data automation and transformation strategy for production-ready pipelines.
Establish reference architectures and engineering standards for ETL/ELT, orchestration, and observability.
Oversee design and implementation of robust, reusable data integration patterns for batch and streaming use cases.
Develop and implement training programs to enhance technical proficiency in data engineering practices.
Ensure all solutions are production-ready with comprehensive documentation, testing, and operational monitoring.

What we're looking for

10+ years of experience in data engineering, integration, or related technical roles
5+ years of leadership experience managing technical teams and delivering complex data solutions
Deep expertise in ETL/ELT design patterns, data pipeline architecture, and workflow orchestration frameworks
Strong knowledge of batch and streaming data processing technologies and modern cloud infrastructure (AWS, Azure, GCP)
Proficiency in programming languages commonly used in data engineering such as Python, SQL, Scala
Understanding of data quality, observability, monitoring systems, and DevOps practices including CI/CD pipelines

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