Digital Data Product Analyst
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.
Requirements:
- Bachelor's degree in information systems, business analysis, or related fields.
- 5+ years of experience in data analysis, business analysis, product analytics, or similar roles.
- Proven ability to work effectively in cross‑functional environments and support the delivery of data products that serve multiple stakeholders.
- Skilled at requirements elicitation, process mapping, and translating business needs into technical specifications.
- Skilled in crafting user stories, acceptance criteria, and high‑quality product and data documentation to support scalable, repeatable workflows.
- Strong understanding of data stewardship principles, including data quality, lineage, metadata management, and responsible data use and the ability to adapt analytical and stewardship skills across a wide range of client use cases.
- Comfortable connecting data across multiple client systems and enriching datasets to enable new insights for sports, fan, and business stakeholders.
- Excellent communication, with the ability to tailor messages for both technical teams (engineering, data science) and business stakeholders (club personnel, league departments).
- Champions a consumer-first mindset, consistently grounding product, data and insights decisions with a deep understanding of consumer behaviors and needs.
- Collaborative mindset with the ability to influence without authority and drive alignment across cross‑functional teams.
- Skilled at navigating ambiguity, asking the right clarifying questions, and moving teams toward clarity and action.
- Naturally curious, with a passion for exploring new data sources, uncovering insights, and improving data quality.
- Strong critical thinking and structured problem‑solving, especially when interpreting incomplete, messy, or evolving datasets.
- Strong analytical toolkit leveraging SQL, Python, and data querying tools to explore, transform, and validate complex datasets that span across multiple product disciplines.
- Working knowledge of data modeling, ETL/ELT pipelines, and cloud data platforms (e.g., Snowflake, Databricks, AWS) to support reliable data products.
- Experience working in digital and D2C environments with exposure to clickstream, customer engagement, and media analytics data, including tools such as Adobe Analytics and Google Analytics.
Benefits:
- For more information on benefits and what we offer please visit us at https://www.exlservice.com/us-careers-and-benefits
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