Digital Data Product Analyst

Role: Digital Data Product Analyst

Location: Remote Canada

Canada, Ontario Province only

Strict instruction from client experience 8 to 12 years max

Job description:

The Data Product Analyst serves as a critical bridge between business stakeholders, analytics teams, and data management groups. This role combines strong data analysis capabilities with core business analysis skills to ensure that data is effectively leveraged to inform strategic decision making, improve processes, and influence solution design. In addition to championing data stewardship, the Data Product Analyst plays a key role in eliciting requirements, documenting business processes, and facilitating alignment across technical and business teams.

Key Responsibilities

1. Act as the Data Subject Matter Expert to stakeholders with an understanding of data across the end to end data supply chain
2. Collect, clean, and analyze data from multiple sources to uncover trends, patterns, and actionable insights.
3. Translate analytical findings into clear, business friendly insights that support decision making.
4. Elicit, document, and manage business, functional, and non functional requirements through techniques such as interviews, workshops, process analysis, and user story creation.
5. Conduct stakeholder analysis to understand needs, roles, dependencies, and expectations across teams.
6. Support prioritization by assessing business value, impacts, complexity, and risk.
7. Ensure traceability of requirements from intake through development, testing, and deployment.
8. Collaborate with data engineering analysts, architects, and engineers to ensure solutions reflect business context and use cases.
9. Define testing acceptance criteria, support user validation, and provide structured feedback for continuous improvement.
10. Monitor and enhance data quality through profiling, validation, remediation, and alignment with organizational priorities.

Key Skills & Competencies

1. Skilled at requirements elicitation, process mapping, and translating business needs into technical specifications and scalable data solutions.
2. Experience supporting the full product and data delivery lifecycle, including requirements gathering, roadmap support, delivery oversight, testing/UAT, launch, hypercare, and ongoing quality monitoring.
3. Skilled in crafting user stories, acceptance criteria, and high-quality product and data documentation to support scalable, repeatable workflows.
4. Strong understanding of data stewardship principles, including data quality, lineage, metadata management, governance, and responsible data use, with the ability to champion data development initiatives that align with stakeholder needs.
5. Experience working across multiple data touchpoints and varying integration patterns within complex digital ecosystems, with the ability to connect and enrich datasets across platforms and systems.
6. Strong understanding of digital and D2C ecosystems, including customer engagement, clickstream, and media analytics data, with exposure to tools such as Adobe Analytics and Google Analytics.
7. Ability to act as a data product leader by balancing stakeholder requirements, technical feasibility, and long-term platform scalability.
8. Excellent communication skills, with the ability to tailor messaging for both technical teams (engineering, data science) and business stakeholders (club personnel, league departments).
9. Strong stakeholder management and collaboration skills, with the ability to influence without authority and drive alignment across cross-functional teams.
10. Champions a consumer-first mindset, consistently grounding product, data, and insights decisions in a deep understanding of consumer behaviors and needs.
11. Skilled at navigating ambiguity, asking the right clarifying questions, and driving teams toward clarity, execution, and measurable outcomes.
12. Naturally curious, with a passion for exploring new data sources, uncovering insights, and continuously improving data quality and processes.
13. Strong critical thinking and structured problem-solving skills, especially when working with incomplete, messy, or evolving datasets.
14. Strong analytical toolkit leveraging SQL, Python, and data querying tools to explore, transform, and validate complex datasets spanning multiple product disciplines.
15. Working knowledge of data modeling, ETL/ELT pipelines, APIs, integration frameworks, and cloud data platforms (e.g., Snowflake, Databricks, AWS) to support reliable and scalable data products.

Qualifications

1. Bachelor's degree in information systems, business analysis, or related fields.
2. 5+ years of experience in data analysis, business analysis, product analytics, or similar roles.
3. Proven ability to work effectively in cross functional environments and support the delivery of data products that serve multiple stakeholders.
4. Experience in sports, media, or entertainment ecosystems, including digital platforms, fan engagement, and/or streaming data environments