Data Quality Engineer QA

DynataHungary only

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Opens the original posting on Himalayas.

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This role is part of our talent pipeline for future hiring needs. While there may not be an immediate opening, we regularly expand our team and are interested in connecting with talented professionals.

Qualified candidates will be invited to meet the Hiring Team and, if successful, will join our talent pool for future opportunities.

This position is open to candidates currently based in Hungary who have the legal right to live and work in the country. Only shortlisted candidates who meet these requirements will be contacted regarding next steps.

THE ROLE

The Data Quality Engineer is responsible for designing and implementing the data quality framework across the enterprise lakehouse platform. This role ensures that data assets meet defined quality standards through automated validation, monitoring, anomaly detection, and incident management, building trust in data across the organization.

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Data Quality Engineer QA at Dynata · ApplyPick

KEY RESPONSIBILITIES
▸ Design and implement a comprehensive data quality framework covering completeness, accuracy, consistency, timeliness, and uniqueness
▸ Build automated data quality test suites using Great Expectations, dbt tests, or Soda Core
▸ Develop data quality dashboards and scorecards to provide visibility to data producers and consumers
▸ Implement anomaly detection and data observability solutions (Monte Carlo, Bigeye, or custom solutions)
▸ Integrate quality checks into CI/CD pipelines to prevent bad data from reaching production
▸ Define and manage SLAs for data quality at the pipeline and data product level
▸ Triage and resolve data quality incidents, coordinating with upstream source owners
▸ Collaborate with data governance team to enforce quality rules aligned with business glossary definitions
▸ Profile new data sources as part of the onboarding process to establish baseline quality benchmarks
▸ Educate data engineering and product teams on data quality standards and measurement approaches
REQUIRED QUALIFICATIONS
▸ 4+ years in data engineering, data quality, or analytics engineering roles
▸ Hands-on experience with data quality tools: Great Expectations, dbt tests, Soda, Monte Carlo, or similar
▸ Strong SQL and Python skills for writing 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 and their application in lakehouse environments
▸ Experience with Airflow or similar orchestration tools to schedule quality jobs
▸ Bachelor's degree in Computer Science, Statistics, Engineering, or related field
PREFERRED QUALIFICATIONS
▸ Experience with Databricks or Snowflake data quality native features
▸ Knowledge of DataHub or data catalog integration for quality score publishing
▸ Familiarity with data contracts and shift-left quality approaches in data mesh architectures

Data Quality Engineer QA

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THE ROLE

Data Quality Engineer QA

Apply now

THE ROLE

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