Senior Technical Product Manager

Senior Technical Product Manager

Prize Picks, the leading DFS platform known for accessibility and a thriving community, is seeking a Senior Technical Product Manager - Data to own the full lifecycle of our internal data platform - from data ingestion and ETL pipelines through dimensional modeling, analytics engineering, and the reporting surface that business stakeholders depend on every day. You will be the connective tissue between non-technical business stakeholders and the combined Analytics Engineering and Data Engineering teams that build for them.

Your work will define data requirements before features ship, compress UAT cycles, hold committed delivery dates, and make the data platform feel like one product to the people who depend on it.

Stakeholder Partnership:

• Serve as the product-accountable owner for the internal data platform - from ingestion through the reporting layer — partnering directly with non-analytics business stakeholders:
  Fraud, Rev Ops, Partnerships, Acquisition, Player Accounts, Accounting, and Finance.
• Capture requirements nslate raw business problems into product framing, scope, and acceptance criteria before delivery starts.
• Engage upstream product teams - gameplay, discovery, growth - to define data event tracking and instrumentation requirements before features go to build. Prevent reporting gaps by owning the data requirements conversation early in the product development lifecycle.

Strategy:

• Own the product roadmap across the full data platform lifecycle: ingestion, ETL pipeline health, dimensional modeling, semantic layer, and the consumer-facing reporting surface.
• Sequence stakeholder requests and platform investments against capacity and business priorities. Identify recurring patterns and turn them into durable mart and view extensions instead of one-off deliverables.
• Stay ahead of upstream product development - define the dimensional models and data requirements needed downstream before new features ship.

Execute:

• Own the end-to-end product lifecycle for data deliverables: discovery, scope, UAT readiness, delivery, and post-launch adoption.
• Partner with Analytics Engineering on data mart and stable view design. Ensure requirements and UAT criteria are clear before AE begins building, so UAT cycles compress and committed dates hold.
• Partner with Data Engineering on pipeline architecture, ETL design, and data quality standards. Translate business requirements into data engineering specs and own the product decisions around pipeline health, SLAs, and failure triage.
• Own go-to-market and stakeholder communications for new and updated data and reporting capabilities.

Collaborate:

• Bridge analytics, analytics engineering, and data engineering conversations so internal consumers experience one product team, not three.
• Champion a data-quality-first culture - surface data trust issues early and drive them to resolution with the right owners.

Industry Knowledge:

• Develop deep familiarity with how each stakeholder function uses data: what decisions it informs, where the gaps live today, and how reporting needs evolve as the business scales.

Lead:

• Report to the Group Product Manager and manage a combined Analytics Engineering and Data Engineering team. Own the scope and roadmap across approximately 14 engineers and analysts.
• Lead architectural conversations with engineering managers. Translate business strategy into platform investment decisions, not just delivery tasks.

Role Specific:

• Strong understanding of data modeling fundamentals: the difference between marts, stable views, and reports — and how each maps to a stakeholder need. Ability to reason about grain, fan-out risk, and dimensional design decisions.
• Working knowledge of ETL and data pipeline concepts: ingestion, transformation layers, data quality validation, and pipeline failure triage. Able to own product decisions around pipeline health without deferring that conversation entirely to engineering.
• Experience engaging upstream product teams on data event tracking and instrumentation requirements before features go to build.
• Track record of translating ambiguous business asks into product scope,…