Working-lead role that owns product definition quality for the highest-complexity opportunities in the Data Products portfolio — output quality across the full lifecycle, from problem framing through Ready-to-Build handoff. Insight is the starting focus. This role sets the standard for the rest of the team by demonstrating it directly, not by directing others’ work.

Scope: Owns product definition quality for the highest-complexity opportunities in the Data Products function, working as an individual contributor. Partners with Platform Engineering, Data Science/ML, and business stakeholders. Sets the standard Solutions Analysts follow — without formal authority over their day-to-day work or performance. Reports to the Director, Data Products.

Essential Job Functions:

Own output quality across the full product definition lifecycle, from problem framing through Ready-to-Build handoff, on the highest-complexity opportunities

Set the standard for what a well-defined opportunity looks like — and demonstrate it directly in your own work

Make the call on what moves forward

Build repeatable methods and templates that Solutions Analysts can execute without your involvement in every decision

Author product definitions, business metric tables, and agent context specs for the highest-complexity opportunities

Lead deployment channel decisions — Databricks-native vs. Teams, Dynamics, or another end-user tool

Maintain the business context layer: metric definitions, metadata, and decision rules that keep AI products reasoning correctly

Represent product definition in cross-functional reviews with Platform Engineering and DS/ML

Raise the judgment of Solutions Analysts through direct feedback, documented standards, and context — without a reporting relationship

Ensure handoffs to Platform Engineering are clean, and define for DS/ML what models must produce and within what constraints

Required:

Bachelor’s degree in a relevant field

7+ years in data, analytics, or product, with deep hands‑on ownership of product definition work end‑to‑end (people‑management experience not required)

Product definition depth — can write a well‑structured product spec, business metric table, and agent context document, and knows the difference between a complete one and one that causes problems downstream

Technical fluency without engineering scope — understands what Databricks, Teams, and Dynamics can do well enough to make deployment decisions,



without reaching into Platform Engineering’s territory

Working‑lead instinct — most effective close to the work, and sets standards by demonstrating them rather than directing others

Influence without authority — can shape how Solutions Analysts and peers approach their work through standards, documentation, and direct coaching, with no reporting relationship

Operating model discipline — manages the boundary with Platform Engineering and DS/ML cleanly, and holds that line under pressure

Hands‑on experience defining AI/agentic products (semantic‑layer or metadata‑driven products)

Familiarity with Databricks, Microsoft Teams, and Dynamics as delivery channels

Authority To:

Set and enforce the Ready-to-Build standard for product definitions

Decide what product definition work moves forward to handoff

Make deployment channel decisions (Databricks-native vs. Teams, Dynamics, or other)

Requires Approval For:

Roadmap changes and new commitments (owned by the Director)

Cross-functional escalations that change Platform Engineering or DS/ML scope

Prioritizing Discovery Analysts’ work (owned by their manager — this role influences, not directs)

Key Contacts: Internal

Director, Data Products

Data Science/ML

Business stakeholders

Discovery Team

External

Technology and platform vendors (e.g., Databricks)

Lottery customers

Physical Requirements: The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions. While performing the duties of this job, the employee is regularly required to sit, stand, walk, bend, use hands, operate a computer, and have specific vision abilities to include close and distance vision, and ability to adjust focus working with computer and business equipment.

Work Conditions: Scientific Games, LLC and its affiliates (collectively, “SG”) are engaged in highly regulated gaming and lottery businesses. As a result,



certain SG employees may, among other things, be required to obtain a gaming or other license(s), undergo background investigations or security checks, or meet certain standards dictated by law, regulation or contracts. In order to ensure SG complies with its regulatory and contractual commitments, as a condition to hiring and continuing to employ its employees, SG requires all of its employees to meet those requirements that are necessary to fulfill their individual roles. As a prerequisite to employment with SG (to the extent permitted by law), you shall be asked to consent to SG conducting a due diligence/background investigation on you.

This job description should not be interpreted as all-inclusive; it is intended to identify major responsibilities and requirements of the job. The employee in this position may be requested to perform other job‑related tasks and responsibilities than those stated above.

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📌 Senior Data Product Owner (Winnipeg)
🏢 Scientific Games
📍 Winnipeg