Are you looking for a Data Quality Engineer job? This position focuses on making enterprise data accurate, complete, consistent and dependable for reporting, analytics and business decision-making.
You will design automated quality controls across a cloud-based data platform and work with data engineers, analysts, architects, data owners and governance specialists. The technical environment includes Azure, Databricks, SQL and Python. This is a specialist position requiring at least four years of relevant professional experience and fluent English. Portuguese is not listed among the requirements.
Your responsibilities
Develop and maintain automated data quality controls across ingestion, transformation, reporting and data product processes.
Create reusable validation components, quality rules, profiling routines and monitoring standards.
Convert business expectations into measurable controls, thresholds and acceptance criteria.
Monitor quality alerts and investigate failed checks.
Perform root-cause analysis and coordinate corrective action with technical and business teams.
Incorporate data quality testing into CI/CD pipelines, orchestration processes and production monitoring.
Document validation rules, test results, exceptions, recurring issues and remediation measures.
Support data profiling, anomaly detection, reconciliation and regression testing.
Validate new data sources and platform changes before they are introduced into production.
Required experience and skills
At least four years of experience in data engineering, data quality engineering, data testing, analytics engineering or data platform delivery.
Advanced SQL and Python skills for validation, profiling, reconciliation, anomaly detection and automated testing.
Practical experience with cloud data technologies such as Azure Data Factory, Azure Data Lake, Databricks, Spark or Delta Lake.
Experience with data quality or observability solutions such as Great Expectations, Databricks Expecta