Associate Technical Product Manager

Ancestry•Draper, UT

6d•Hybrid

About The Position

Ancestry's Data, AI & Analytics Platforms team is the bridge between raw data and trusted business decisions. In this role, you will act as a Bridge Builder and Steward, ensuring that governed, high-quality data flows from our platforms into Finance reporting, analyst workflows, and AI-driven applications. You will sit at the intersection of Data Governance, Data Quality, and Analytics Enablement — partnering daily with stakeholders across Governance, EDM, Finance, and the analyst community. This is a high-impact entry point into technical product management on a team that operates as Bridge Builders and Stewards of the enterprise's intelligence.

Requirements

Bachelor's degree in Computer Science, Analytics, Information Systems, Data Engineering, or a related field.
1–3 years in product management, program management, business analyst, data analyst, or technical operations roles. New grads with strong relevant internships will be considered.
Working knowledge of SQL, the data lifecycle, and concepts like data lineage, schema validation, and metric definitions.
Genuine interest in data stewardship, compliance, and the discipline of "ready-for-use" data assets.
Ability to translate between business stakeholders (Finance, Analytics) and technical teams (Engineering, Data Platform).
Strong written and verbal communication.
Comfortable working with data to inform prioritization decisions; able to translate platform metrics into stakeholder-friendly insights.
Exposure to Agile/Scrum methodologies and tools like Jira or Rally.
Detail-oriented, organized, comfortable with ambiguity, and motivated by operational excellence.

Nice To Haves

Internship or co-op experience in a data-centric, analytics, or platform PM environment.
Familiarity with data catalog, BI, or data warehouse platforms (e.g., Alation, Tableau, Redshift, Snowflake).
Exposure to compliance frameworks (SOX, GDPR, CCPA).
SOX or audit exposure is a plus.

Responsibilities

Steward Data Governance — Support the intake, definition, and lifecycle management of business metrics and governance protocols, ensuring adherence to compliance and audit standards.
Drive Data Quality — Partner with engineering on automated quality checks, schema validations, and remediation workflows; monitor outcomes through established observability frameworks.
Enable Analytics Partners — Collaborate with Analytics Engineering and Product Analytics teams to deliver platform features that accelerate self-service, reduce time-to-insight, and standardize trusted metrics.
Support Platform Migrations — Help track stakeholder adoption, usage telemetry, and communications for legacy tool deprecations and new capability rollouts.
Triage Business Requests — Manage incoming stakeholder requests with clear prioritization frameworks, ensuring the team builds the "right things at the right time."
Document Rigorously — Create and maintain feature requirements, technical specifications, user stories, and governance documentation.
Operational Excellence — Track key platform metrics including data freshness, pipeline uptime, and quality SLAs to ensure a healthy, trusted foundation.
Apply AI-First Principles — Use AI-augmented PM workflows in your daily work and contribute to the team's AI literacy commitment.