✦ Luna Orbit — Data & Analytics

Senior Technical Product Manager, Data Engineering & Data Science Solutions

at S&P Global

📍 3 Locations Unknown 💰 $100K – $149K USD / year Posted March 25, 2026
Salary $100K – $149K USD / year
Type Not Specified
Experience senior
Exp. Years 8+ years
Education Bachelor's in Computer Science or related field
Category Data & Analytics

This role involves leading the development of enterprise-grade data platforms, managing cross-functional teams, and implementing advanced data infrastructure and MLOps practices to support analytics and machine learning initiatives.

  • Drive product strategy and roadmap for data infrastructure
  • Lead cross-functional teams for data engineering capabilities
  • Implement MLOps practices for model lifecycle
  • Collaborate on knowledge management and semantic data
  • Champion data quality initiatives

The technical environment includes Databricks, cloud platforms (AWS, Azure, GCP), Apache Spark, Kafka, Airflow, and MLOps tools, focusing on scalable data pipelines, data quality, and model lifecycle management.

The ideal candidate is a senior data platform professional with extensive experience in building scalable data infrastructure, proficient in Databricks, cloud platforms, and MLOps practices, with a strong background in product management and cross-functional collaboration.

Bachelor's degree in Computer ScienceEngineeringData Scienceor related field8+ years of product management experienceHands-on experience with Databricks featuresExperience with data engineering technologiesExperience with cloud data platformsUnderstanding of MLOps processesKnowledge of SDLC methodologiesAbility to translate business requirements into technical specifications
Advanced degree (MBAMS)Experience with data governance framework
DatabricksMLflowApache SparkKafkaAirflowAWSAzureGoogle Cloud Platform
Bachelor's in Computer Science or related field8+ years product managementDatabricksDelta LakeMLflowApache SparkKafkaAirflowAWSAzureGoogle Cloud PlatformMLOpsSDLCAgileScrumDevOps
DatabricksDelta LakeMLflowDatabricks SQLApache SparkKafkaAirflowAWSAzureGoogle Cloud PlatformMLOpsSDLCAgileScrumDevOps
collaborationend user empathyhard workhonestycommunicationleadershipproblem-solvingteamwork
Industry Financial Services / Data Analytics
Job Function Leading data platform development and management for enterprise analytics
Role Subtype Data Engineer
Tech Domains Apache Spark, Amazon Web Services, Azure, Google Cloud Platform, Databricks, MLflow, Kafka, Airflow
product managementdata platformsanalytics infrastructureenterprise data solutionsDatabricksDelta LakeMLflowApache SparkKafkaAirflowAWSAzureGoogle Cloud PlatformMLOpsSDLCAgileScrumDevOps

Lack of experience with Databricks or cloud platforms, Less than 8 years of relevant experience, No experience with MLOps or data engineering tools, No degree in relevant technical fields

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