Data Quality Engineer, QA

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Dynata

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

💼 Consulting

📣 Marketing

☁️ SaaS

💰 $31.5M Debt Financing - Dynata on 2024-05

Consulting • Marketing • SaaS

Dynata is a market research and data company that provides high-quality first-party survey panels, audience data, and a suite of survey and analytics platforms to help organizations collect, activate, and measure insights. The company offers global B2B and B2C panels, survey scripting and fielding tools, data enrichment, audience activation, brand lift measurement, and data visualization, and it emphasizes data quality using AI/ML (QualityScore™) and security certifications. Dynata serves researchers, brands, media agencies, publishers, pollsters, and academics with both self-service and managed services.

📋 Description

• Design and implement a comprehensive data quality framework across the enterprise lakehouse platform • Build automated data quality test suites using Great Expectations, dbt tests, or Soda Core • Develop data quality dashboards and scorecards for data producers and consumers • Implement anomaly detection and data observability solutions • Integrate quality checks into CI/CD pipelines • Define and manage data quality SLAs at pipeline and data product levels • Triage and resolve data quality incidents with upstream source owners • Collaborate with the data governance team to enforce quality rules aligned with business glossary definitions • Profile new data sources during onboarding and establish baseline quality benchmarks • Educate data engineering and product teams on data quality standards and measurement approaches • Participate in the recruitment process and, if successful, join the talent pool for future openings

🎯 Requirements

• 4+ years in data engineering, data quality, or analytics engineering roles • Hands-on experience with Great Expectations, dbt tests, Soda, Monte Carlo, or similar data quality tools • Strong SQL and Python skills for validation logic and quality metric queries • Experience with Apache Spark or dbt for large-scale data transformation and testing • Familiarity with data profiling techniques and statistical approaches to anomaly detection • Knowledge of data observability concepts in lakehouse environments • Experience with Airflow or similar orchestration tools • Bachelor's degree in Computer Science, Statistics, Engineering, or related field • Experience with Databricks or Snowflake data quality native features preferred • Knowledge of DataHub or data catalog integration preferred • Familiarity with data contracts and shift-left quality approaches in data mesh architectures preferred • Currently based in Hungary • Legal right to live and work in Hungary

🏖️ Benefits

• Competitive salary • Comprehensive range of benefits tailored to Hungary • Support for well-being and healthy work-life balance • Collaborative, inclusive culture • Opportunities for growth • Global Power Your Career conference for employees to connect, learn, and grow • High-Potential Program with immersive, hands-on professional development • Leadership Challenges providing skills and insights for managers and future leaders