Data Quality Engineer

About MediaRadar MediaRadar , equips marketing, sales and analytics leaders with the intelligence they need to stay ahead. Our platform delivers always-on, AI-enabled Creative, Competitive, Commercial and Market Intelligence—spanning ad strategy, media spend, creative assets and brand messaging across 30+ media channels and five million brands. With deep insights into more than 35 million ad and campaign assets and $280 billion in media spend, MediaRadar provides a single, interoperable source of truth that plugs seamlessly into enterprise analytics and AI systems. The result: faster, cleaner and more actionable intelligence that drives competitive advantage. Job Summary We are seeking a Data Quality Engineer to build and operate the tooling that makes data quality measurable, automated, and continuous. Where the auditor assesses quality and governance defines the rules, this role builds the instrumentation — automated checks, monitoring, and dashboards that test governed data against rules at scale and surface issues the moment they appear. This is a hands-on engineering role embedded in a lean quality function. You will translate governance rules and quality thresholds into executable tests, integrate them into data pipelines and platforms, and give the organization always-on visibility into the health of its data. You partner with Governance, Data Operations, and platform teams to embed quality into how data moves rather than checking it after the fact. Responsibilities Translate authored data rules and quality thresholds into automated, executable quality checks. Build and maintain data quality monitoring, alerting, and dashboards across governed datasets. Integrate quality checks into data pipelines, classification workflows, and governance tooling. Automate detection of rule conflicts, duplicates, and reference data anomalies at scale. Develop tooling that supports auditors, analysts, and stewards in their day-to-day work. Instrument human-in-the-loop workflows to capture validation outcomes and quality signals. Maintain reliable, performant data quality infrastructure and supporting data flows. Partner with Governance to make rules executable and to close gaps between definition and enforcement. Success in this role will be measured by: Automated Coverage – Growing share of rules and thresholds enforced by automated checks rather than manual review. Timeliness – Quality issues surfaced in near-real-time through monitoring and alerting. Reliability – Stable, performant quality infrastructure and trustworthy metrics. Enablement – Tooling that measurably improves auditor, analyst, and steward productivity. Embeddedness – Quality checks integrated into production pipelines and workflows, not bolted on. Issue Reduction – Measurable decline in quality issues reaching downstream consumers. Key Qualifications and Role Requirements 4–8 years in data engineering, data quality engineering, analytics engineering, or a related field. Strong programming skills (e.g., Python, SQL) and experience building data pipelines or automation. Experience implementing automated data quality checks, testing, or monitoring frameworks. Familiarity with data quality dimensions and how to operationalize them in code. Comfort working with cloud data platforms, APIs, and governance/quality tooling. Ability to translate written rules and standards into executable logic. Exposure to AI/ML-assisted classification and human-in-the-loop systems a plus. Strong communication skills and a collaborative, enablement-oriented mindset. At MediaRadar, we are committed to creating an inclusive and accessible workplace where everyone can thrive. We believe that diversity of backgrounds, perspectives, and experiences makes us stronger and more innovative. We are proud to be an Equal Opportunity Employer and make employment decisions without regard to race, color, religion, sex (including pregnancy, sexual orientation, or gender identity), national origin, age, disability, genetic information, or any other legally protected status. In accordance with the EEO-1 reporting requirements, we collect demographic data as part of our efforts to ensure fair and equitable hiring practices across all levels of our organization. A final compensation offer will ultimately be based on the candidate's location, skill level and experience, and the Company's pay equity. We are also committed to ensuring our recruitment process is accessible to all applicants. If you need a reasonable accommodation during the application or interview process, please contact us at [email protected] . We’re excited to meet people who share our values and want to build the future with us.