{"id":104742,"url":"https://alion.io/job/ahead-data-governance-lead","title":"Data Product Governance Lead","company":{"id":3614,"name":"AHEAD","domain":"ahead.com","url":"https://alion.io/company/ahead","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":{"grade":"B","score":75,"open_postings":46,"ghost_share":0,"stale_share":0.783,"repost_share":0,"time_to_fill_p50_days":73,"computed_at":"2026-10-25T05:49:26Z"}},"role":"DevOps","role_family":"DevOps","seniority":"lead","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":150000,"max":175000,"currency":"USD","period":"year","gross":null,"usd_annual":175000},"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Snowflake","optional":false},{"name":"Apache Kafka","optional":true},{"name":"Apex","optional":true},{"name":"CI/CD","optional":true},{"name":"MuleSoft","optional":true},{"name":"Platform Engineering","optional":true}],"status":"live","first_seen_at":"2026-08-04T14:31:30Z","employer_posted_date":"2026-08-04","last_verified_at":"2026-10-25T18:06:06Z","board_verified":true,"closed_at":null,"days_open":82,"trust":{"level":"ok","repost_count":1,"flags":[],"days_open":81},"description":"The Data Product Governance Lead is responsible for developing and operationalizing the standards and capabilities that make data products on AHEAD's Data Platform discoverable, trusted, and ready for use. The Lead defines publication requirements and owns the product roadmap for catalog, lineage, metadata, certification, and related governance capabilities. The role works hands-on in Snowflake and closely with Data Platform engineers to build these requirements into the platform and automate checks where practical.\nThe role sits within the Data Platform Team and reports to the Director, Data Platform. The Lead will support AHEAD's federated data product model by turning policy, platform standards, and user needs into clear requirements for data publishers and consumers.\nThis leader will also build and lead a small governance function over time as the platform matures.\nDuties and Responsibilities\nData Product Standards and Publication\nDefine the standards a data product must meet before it is published for broader consumption, and update those standards as the platform and its consumers evolve.\nEstablish the required information for published data products, including business and technical definitions, ownership, authoritative source, refresh expectations, lineage, quality measures, classification, access requirements, and applicable data contracts.\nDefine publication and certification standards that align with AHEAD's medallion architecture, including the requirements data must meet as it progresses from raw and standardized layers to trusted, reusable data products.\nDefine and maintain publication criteria for data products contributed by domain teams and work with Data Platform engineers to automate those checks where practical.\nDefine certification and readiness indicators that show consumers whether a data product is supported, current, and appropriate for use, including how changes in quality, freshness, or ownership affect that status.\nCreate reusable templates, patterns, and guidance that help domain teams meet publication requirements consistently.\nMetadata, Lineage, Quality, and Contract Standards\nEstablish metadata standards that give consumers useful business and technical context without creating unnecessary documentation overhead.\nDefine lineage requirements across source systems, ingestion, transformation layers, published data products, and downstream consumption, and identify gaps where automated capture needs to improve.\nDefine data quality requirements for published data products, including measures for freshness, completeness, validity, consistency, and reliability, and establish a common way to represent quality and health across the platform.\nPartner with domain teams and engineers to implement dataset-specific quality rules, thresholds, and monitoring, and make quality status visible to consumers through the catalog.\nDefine standards for data contracts, including schema, semantics, ownership, service expectations, versioning, and change management across batch, API, and event-driven data products.\nEstablish clear expectations for changes to published data products so downstream consumers can prepare for them.\nClassification, Access, and Governed Data Use\nTranslate enterprise classification and access standards into data product requirements and platform controls.\nWork with Snowflake capabilities, including RBAC, tagging, classification, masking, and row- and column-level controls, to protect PII and other restricted information.\nDevelop repeatable access patterns that support self-service consumption while maintaining appropriate controls.\nImplement data product governance requirements that support approved AI and agent-based consumption, including sensitive data handling, access, and traceability.\nWork with Security, Risk, Legal, and Architecture teams to align data product governance with privacy, security, compliance, and enterprise requirements.\nProduct Ownership\nCatalog, Lineage, and Governance CapabilitiesOwn the backlog and roadmap for the data catalog, metadata, lineage, publication, certification, and related governance capabilities.\nWork hands-on with Snowflake Horizon Catalog and other platform capabilities used for discovery, metadata, lineage, classification, and trust.\nTreat data publishers and consumers as customers of the Data Platform, regularly gathering feedback to understand friction, unmet needs, and opportunities to improve the publishing and consumption experience.\nTranslate publisher and consumer feedback into prioritized platform requirements and enhancements for the engineering team.\nDefine and monitor measures such as metadata completeness, lineage coverage, quality coverage, certified product adoption, catalog usage, and time to publish, and use feedback and adoption data to improve the platform and standards.\nPartnership and Enablement\nWork directly with Data Platform engineers throughout design and delivery, reviewing designs for governance fit and writing clear acceptance criteria.\nPartner with source-system and domain teams to identify authoritative sources and establish scalable publication patterns that support the federated model.\nHelp establish clear ownership and accountability for published data products across business and technology teams.\nCollaborate with Analytics, Software Engineering, Architecture, Security, and business teams on data product requirements and platform improvements.\nContribute to AHEAD's broader data governance strategy and priorities as the platform evolves.\nEducation and Experience\nBachelor's degree or equivalent practical experience.\n7+ years of experience across data governance, data products, data platforms, data architecture, analytics engineering, technical product management, or related disciplines.\nHands-on experience implementing governance capabilities, including catalog, metadata, and lineage, in a modern cloud data platform.\nExperience defining and implementing data product standards, including ownership, certification criteria, documentation requirements, discoverability, and lifecycle management.\nExperience defining data quality and data contract standards, including measures such as freshness and completeness, schema versioning, and change management.\nWorking knowledge of platform governance controls such as RBAC, data classification, masking, and row- and column-level access.\nExperience owning a technical product backlog or roadmap and prioritizing work based on user and business needs.\nExperience working directly with data engineers, including translating policy and user needs into engineering-ready requirements.\nStrong communication skills and the ability to influence business and technology teams that do not report to you.\nPreferred Experience\nExperience with Snowflake or Snowflake Horizon Catalog, or comparable catalog and lineage platforms.\nExperience with medallion architecture and data product publication patterns in a modern data platform.\nExperience automating metadata, quality, contract, or publication requirements through pipelines, APIs, CI/CD, or platform tooling.\nExperience with federated or domain-oriented data product models.\nExperience in regulated, security-sensitive, or compliance-driven environments, or with PII and other sensitive enterprise data.\nExperience governing schemas and contracts for streaming or messaging environments such as Kafka or MuleSoft.\nExperience developing self-service data discovery, publishing, or access capabilities.\nFamiliarity with governing data for AI and agent-based use cases.\nPhysical Requirements\nAbility to safely and successfully perform the essential job functions consistent with the ADA, FMLA and other federal, state and local standards, including meeting qualitative and/or quantitative productivity standards.\nAbility to maintain regular, punctual attendance consistent with the ADA, FMLA and other federal, state, and local standards.\nPrimarily office and computer-based work with standard technical leadership and collaboration expectations for a platform engineering role.","description_format":"text","description_chars":8076,"description_truncated":false,"requirements":{"experience_years_min":7,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["IT 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