Senior Technical Product Manager – Data Engineering, Data Science Solutions

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🕒 March 24

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S&P Global

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1860

💸 Finance

🏢 Enterprise

🤖 Artificial Intelligence

Finance • Enterprise • Artificial Intelligence

S&P Global is a leading provider of market intelligence, ratings, analytics, and benchmark indices. The company offers comprehensive insights across various domains including finance, commodities, mobility, and sustainability. Renowned for its data-driven solutions, S&P Global assists organizations in navigating complex market trends, evaluating credit risk, and understanding the implications of artificial intelligence and energy transitions. Its diverse offerings, such as S&P Global Market Intelligence, S&P Global Ratings, and S&P Dow Jones Indices, provide critical data and analytics to businesses, government entities, and investors worldwide.

📋 Description

• Drive product strategy and roadmap for critical data infrastructure components, including data onboarding, storage solutions, and core platform engines • Lead cross-functional teams to deliver data engineering capabilities, admin utilities, and data quality solutions that enable enterprise-scale analytics • Own product vision for disaster recovery and resiliency frameworks to ensure platform reliability and business continuity • Define and execute an ontology integration strategy to enhance knowledge management excellence and semantic data capabilities • Collaborate with engineering teams to implement MLOps practices for machine learning operations and model lifecycle management • Develop and maintain an innersource ecosystem strategy to enable cross-team collaboration on core platform capabilities within defined governance guardrails • Partner with stakeholders to define requirements for common data pipeline capabilities and shared tooling that data engineering teams utilize when building enterprise data workflows • Champion data quality initiatives and drive technical implementation of data quality tools and monitoring solutions that ensure accuracy and consistency across all data processing workflows

🎯 Requirements

• Bachelor’s degree in Computer Science, Engineering, Data Science, or related technical field, or equivalent professional experience • 8+ years of product management experience focused on data platforms, analytics infrastructure, or enterprise data solutions • Hands-on experience with advanced Databricks features, including Delta Lake, MLflow, and Databricks SQL for end-to-end data and ML pipeline management • Strong technical background with hands-on experience in data engineering technologies such as Apache Spark, Kafka, Airflow, or similar distributed processing frameworks • Proven experience with cloud data platforms, including AWS, Azure, or Google Cloud Platform • Understanding of Machine Learning Operations (MLOps) processes, including model deployment, monitoring, and lifecycle management • Strong knowledge of standard Software Development Life Cycle (SDLC) methodologies, including Agile, Scrum, and DevOps practices • Demonstrated ability to translate business requirements into technical product specifications while working closely with cross-functional engineering teams

🏖️ Benefits

• Health & Wellness: Health care coverage designed for the mind and body. • Flexible Downtime: Generous time off helps keep you energized for your time on. • Continuous Learning: Access a wealth of resources to grow your career and learn valuable new skills. • Invest in Your Future: Secure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. • Family Friendly Perks: It’s not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. • Beyond the Basics: From retail discounts to referral incentive awards—small perks can make a big difference.