Senior Technical Product Manager, Data Engineering & Data Science Solutions

S&P Global

Quick summary

Work type
On-site
Location
New York, NYBoulder, COPrinceton, NJ
Salary
$100,000–$149,000 / yr
Posted
1 day ago
Closes
Jul 19, 2026
Nearby
99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $193k
This role $124k
$84k most similar roles pay here $246k

This role pays less than 98% of similar roles. Most pay $165,500–$221,137 — the shaded band above. At the midpoint, this role pays about $124k versus about $193k 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 22 open roles on FindRole.

Listed pay typically runs $149,031–$225,000 across 16 roles with salary data.

Most-posted roles

View all roles at S&P Global

At a glance

TL;DR · Senior Technical Product Manager, Data Engineering & Data Science Solutions

Role Posting Log in to save

As a Senior Technical Product Manager in the Data Engineering & Data Science Solutions team at S&P Global Energy, you will drive product strategy and roadmap for critical data infrastructure components such as data onboarding, storage solutions, and core platform engines. Your day-to-day responsibilities include leading cross-functional teams to deliver advanced data engineering capabilities, admin utilities, and disaster recovery frameworks, while also championing MLOps practices and defining requirements for common data pipeline tools. You will work with cutting-edge technologies like Databricks Delta Lake, MLflow, Apache Spark, Kafka, Airflow, and cloud platforms such as AWS, Azure, or Google Cloud Platform. This role requires a strong technical background in data engineering and analytics infrastructure, along with experience in enterprise-scale solutions and regulatory compliance within the financial services sector.

Skills

Databricks Delta Lake MLflow Apache Spark Kafka Airflow AWS Azure Google Cloud Platform MLOps Agile Scrum DevOps CI/CD

What you'll do

  • Drive product strategy and roadmap for critical data infrastructure components.
  • Lead cross-functional teams to deliver enterprise-scale analytics solutions.
  • Own product vision for disaster recovery frameworks ensuring platform reliability.
  • Define and execute ontology integration strategies for semantic data capabilities.
  • Champion data quality initiatives and implement monitoring solutions.
  • Develop innersource ecosystem strategy for cross-team collaboration on platforms.
  • Partner with stakeholders to define requirements for common data pipeline tools.

What we're looking for

  • 8+ years of product management experience in data platforms or analytics infrastructure.
  • Hands-on expertise with advanced Databricks features like Delta Lake, MLflow, and Databricks SQL.
  • Strong background in data engineering technologies including Apache Spark, Kafka, Airflow.
  • Proven experience with cloud data platforms such as AWS, Azure, or Google Cloud Platform.
  • Understanding of MLOps processes for model deployment, monitoring, and lifecycle management.

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