Program Manager, Data Quality & Standards

Career Guide

A Program Manager, Data Quality & Standards leads cross-team efforts to improve how an organization defines, measures, and maintains high-quality data. The role sets common data rules and definitions, coordinates initiatives that reduce errors and inconsistencies, and ensures teams can trust data for reporting, analytics, and day-to-day operations.

Key Responsibilities

Define and roll out data standards (common definitions, naming rules, formats, and acceptable values) across systems and teams
Establish data quality goals and success metrics (accuracy, completeness, timeliness, consistency) and track progress over time
Run data quality programs and roadmaps: prioritize initiatives, manage timelines, and coordinate stakeholders
Partner with data engineering, analytics, product, and business teams to identify root causes of data issues and drive fixes
Create governance processes for approving changes to data definitions and key metrics to prevent “multiple versions of the truth”
Set up monitoring and alerting for data quality issues and define response processes (triage, ownership, resolution timelines)
Support audits and compliance needs by improving traceability (where data comes from, how it changes, who owns it)
Document standards and processes and deliver training so teams apply them consistently

Top Skills for Success

Program management (roadmaps, dependencies, risk management, stakeholder updates)

Clear communication and influence across technical and non-technical teams

Process design (how work flows, who approves changes, how issues get resolved)

Data literacy (tables, metrics, basic querying, understanding pipelines at a high level)

Data quality methods (profiling data, defining rules, measuring and monitoring quality)

Data governance and operating models (ownership, decision rights, change control)

Metadata and documentation practices (data dictionaries, metric definitions, lineage basics)

Issue management (intake, triage, prioritization, and driving fixes to closure)

Basic understanding of privacy and security expectations (what data is sensitive and how it should be handled)

Career Progression

Can Lead To

Senior Program Manager, Data Governance

Data Governance Lead / Manager

Senior Product Manager, Data Platform (governance/quality focus)

Director, Data Quality / Data Governance

Transition Opportunities

Data Product Manager (owning core datasets and metrics)

Analytics Engineering Manager (if building strong technical depth)

Business Operations / Strategy roles (if focusing on process and decision-making)

Compliance / Risk roles in data-heavy regulated industries

Common Skill Gaps

Often Missing Skills

Hands-on ability to validate data (basic SQL or equivalent) rather than relying only on othersTurning business definitions into concrete data rules and measurable checksOperationalizing monitoring (who gets alerts, what happens next, and how repeat issues are prevented)Change management (driving adoption of standards across teams with different priorities)Clear ownership models for shared data (who is accountable when issues span systems)

Development SuggestionsBuild a small portfolio of artifacts employers expect: a data standards playbook (definitions + examples), a data quality scorecard (metrics + targets), and a simple issue intake-to-resolution workflow. Pair that with enough querying and dashboarding skill to independently investigate common quality issues.

Salary & Demand

Median Salary Range

Entry LevelUS: $90k–$120k (often requires prior data/ops experience even at “entry”)

Mid LevelUS: $120k–$165k

Senior LevelUS: $165k–$220k+ (higher at large tech/finance; may include bonus/equity)

Growth Trend

Growing demand. Organizations are investing more in reliable data for analytics/AI, regulatory readiness, and operational efficiency, which increases hiring for data governance and data quality program leadership.

Companies Hiring

Major Employers

AmazonMicrosoftGoogleMetaAppleSalesforceIBMOracleJPMorgan ChaseBank of AmericaUnitedHealth GroupCVS HealthWalmart

Industry Sectors

Technology and SaaSFinancial services and insuranceHealthcare and life sciencesRetail and e-commerceTelecommunicationsManufacturing and logisticsGovernment and education

Recommended Next Steps

Create a 30-60-90 day plan template for a data quality program (assessment, quick wins, longer-term standards rollout)

Practice translating a messy metric into a standardized definition and quality checks (e.g., “active customer,” “net revenue”)

Strengthen practical data skills: be able to run basic queries and interpret results to confirm issues and measure improvements

Develop stakeholder stories for interviews: one example each of resolving a cross-team data issue, setting a standard, and driving adoption

Learn common data documentation approaches (data dictionary + metric catalog) and draft a sample for a dataset you know

Target roles in data-heavy organizations where governance is a priority (finance, healthcare, large SaaS) and tailor your resume to outcomes (reduced defects, faster reporting, fewer reconciliation issues)