{"id":1622747,"url":"https://alion.io/job/exl-digital-data-product-analyst","title":"Digital Data Product Analyst","company":{"id":38016,"name":"EXL","domain":"exlservice.com","url":"https://alion.io/company/exl","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"B","score":76,"open_postings":247,"ghost_share":0,"stale_share":0.98,"repost_share":0,"time_to_fill_p50_days":29,"computed_at":"2026-11-10T06:52:35Z"}},"role":"Analytics","role_family":"Analytics","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":81000,"max_usd":155000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":2036},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Databricks","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-08-24T22:16:44Z","employer_posted_date":"2026-08-24","last_verified_at":"2026-11-10T22:54:50Z","board_verified":true,"closed_at":null,"days_open":78,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":78},"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.\n Act as the Data Subject Matter Expert to stakeholders with an understanding of data across the end-to-end data supply chain\nCollect, clean, and analyze data from multiple sources to uncover trends, patterns, and actionable insights.\nTranslate analytical findings into clear, business-friendly insights that support decision-making.\nElicit, document, and manage business, functional, and non-functional requirements through techniques such as interviews, workshops, process analysis, and user story creation.\nConduct stakeholder analysis to understand needs, roles, dependencies, and expectations across teams.\nSupport prioritization by assessing business value, impacts, complexity, and risk.\nEnsure traceability of requirements from intake through development, testing, and deployment.\nCollaborate with data engineering analysts, architects, and engineers to ensure solutions reflect business context and use cases.\nDefine testing acceptance criteria, support user validation, and provide structured feedback for continuous improvement.\nMonitor and enhance data quality through profiling, validation, remediation, and alignment with organizational priorities.\n Bachelor's degree in information systems, business analysis, or related fields.\n5+ years of experience in data analysis, business analysis, product analytics, or similar roles.\nProven ability to work effectively in cross-functional environments and support the delivery of data products that serve multiple stakeholders.\nSkilled at requirements elicitation, process mapping, and translating business needs into technical specifications.\nSkilled in crafting user stories, acceptance criteria, and high-quality product and data documentation to support scalable, repeatable workflows.\nStrong 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.\nComfortable connecting data across multiple client systems and enriching datasets to enable new insights for sports, fan, and business stakeholders.\nExcellent communication, with the ability to tailor messages for both technical teams (engineering, data science) and business stakeholders (club personnel, league departments).\nChampions a consumer-first mindset, consistently grounding product, data and insights decisions with a deep understanding of consumer behaviors and needs.\nCollaborative mindset with the ability to influence without authority and drive alignment across cross-functional teams.\nSkilled at navigating ambiguity, asking the right clarifying questions, and moving teams toward clarity and action.\nNaturally curious, with a passion for exploring new data sources, uncovering insights, and improving data quality.\nStrong critical thinking and structured problem-solving, especially when interpreting incomplete, messy, or evolving datasets.\nStrong analytical toolkit leveraging SQL, Python, and data querying tools to explore, transform, and validate complex datasets that span across multiple product disciplines.\nWorking knowledge of data modeling, ETL/ELT pipelines, and cloud data platforms (e.g., Snowflake, Databricks, AWS) to support reliable data products.\n 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 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