Data Platform Product Manager

Data Platform Product Manager

Location

Offshore or Nearshore (remote)

Type of Role

Contract (Staff Augmentation)

Time Zone

Must overlap with Eastern Time (EST) working hours

Overview

An organization is seeking a Data Platform Product Manager to own the strategy, roadmap, and lifecycle of its enterprise data platforms and data integration capabilities across ETL and ELT patterns. The role drives the evolution, adoption, and value of cloud and relational data platforms, including Snowflake, Azure Data Lake, SQL Server, PostgreSQL, and Oracle.

The Product Manager will work closely with Architecture, Data Engineering, Data & Analytics, Cloud Engineering, Security, and Finance to keep these platforms scalable, reliable, secure, cost-effective, and aligned to enterprise priorities. The work is done in a regulated, high-sensitivity data environment. Offshore and nearshore candidates are welcome, provided they can work with meaningful overlap with EST hours.

Key Responsibilities

• Own the enterprise data platform roadmap, sequencing initiatives by business priority, technical readiness, and value delivery.
• Provide end-to-end product ownership for data storage, processing, and integration platforms, including feature prioritization, backlog management, and lifecycle decisions.
• Partner with Architecture and Engineering to define platform standards, reference architectures, design patterns, and operational practices.
• Work with Finance on the annual budget forecast, with a view toward a 3–5 year budget cycle.
• Manage cost models, usage transparency, and capacity planning, optimizing platform spend with Finance and Cloud Engineering.
• Work with Security, Risk, and Compliance to embed security, privacy, and governance requirements into platform design and operations.
• Drive platform adoption and enablement through better usability, documentation, and onboarding for data producers and consumers.
• Define success metrics (reliability, performance, cost efficiency, adoption, satisfaction) and use them to guide prioritization, while monitoring emerging data platform trends.

Required Experience & Skills

• Bachelor's degree in Computer Science, Information Systems, Data/Analytics, Engineering, Business, or a related field, or equivalent experience.
• 3–5 years of experience in product management or product ownership within technology, data, analytics, or platform teams.
• Proven experience translating business needs into a data platform roadmap and backlog, covering cloud data platforms, ELT/ETL, reliability, governance, and cost optimization.
• Technical fluency in cloud data warehousing/lakehouse, ELT/ETL, orchestration, metadata, observability, and SLAs/SLOs.
• Strong understanding of the product management lifecycle for technical platforms, from discovery and business case through delivery and retirement.
• Strong analytical skills, including using data to define KPIs and measure adoption and platform health.
• Strong business acumen, with the ability to communicate tradeoffs and prioritize using value, risk, and cost inputs.
• Excellent written and verbal communication, including product documentation such as vision, roadmaps, requirements, and release notes.
• Strong organizational and time management skills, with a bias toward execution and the ability to remove blockers.
• Ability to manage governance and operational expectations for shared platforms, including risk management, vendor coordination, and incident prioritization.
• Ability to work with overlap with EST hours for stakeholder meetings and collaboration.

Nice to Have

• Experience with Agile product development (Scrum/Kanban).
• Hands-on familiarity with Snowflake, Azure Data Lake/ADLS, Fabric, Databricks, SQL Server, PostgreSQL, or Oracle.
• Working knowledge of SQL, data modeling, ELT/ETL and orchestration tooling, and CI/CD for data.
• Experience with data governance, security, and privacy controls in regulated environments.
• Experience with cloud cost management/FinOps, including chargeback/showback models.
• Experience using AI tools to support platform analysis, documentation, and product workflows.