- Company Name
- EFFEKTIV
- Job Title
- Data Quality Engineer F/H
- Job Description
-
**Job Title**
Data Quality Engineer (F/M)
**Role Summary**
Lead data quality and reliability initiatives within the data team. Design, implement, and maintain a testing framework (dbt), develop metrics, dashboards, and monitoring alerts to ensure that all data used by the organization is trustworthy, well‑documented, and governed throughout the analytic pipeline.
**Expectations**
- Champion data quality across the entire analytic chain
- Develop and evolve data quality standards, SLAs, and best‑practice guidelines
- Drive cross‑functional collaboration with data engineering, analytics, and business stakeholders to resolve quality incidents
**Key Responsibilities**
- Own and continuously improve data quality across the entire analytic pipeline
- Design, structure, and maintain a dbt‑based testing framework (unit, contractual, business tests)
- Create quality metrics, dashboards, and alerts for monitoring data freshness, join integrity, source‑to‑sink accuracy, and compliance
- Investigate, diagnose, and remediate data quality issues (latency, join failures, data entry errors, compliance gaps)
- Lead incident management in collaboration with business and data engineering teams
- Deploy observability and data cataloguing tools (e.g., Soda, Great Expectations, Monte Carlo)
- Formalize and track data quality SLAs and hold teams accountable
- Contribute to technical debt reduction and standardisation of data practices across the organization
**Required Skills**
- Advanced SQL and extensive experience with dbt
- Proficiency with an orchestration tool (Airflow, Dagster, etc.)
- Familiarity with data‑quality and observability platforms (Soda, Great Expectations, Monte Carlo)
- Strong understanding of analytical data models
- Excellent communication, teaching, and stakeholder‑engagement abilities
- High attention to detail, rigor, and a collaborative mindset
- Leadership across cross‑functional teams without direct management authority
**Required Education & Certifications**
- Degree in Computer Science, Data Science, Information Systems, or related field (equivalent professional experience accepted)
- Certifications in data‑engineering or data‑quality tools (e.g., dbt, Airflow, Great Expectations) preferred but not mandatory.