Data Quality Engineer

We are looking for a Senior Data Quality Engineer to ensure our enterprise data is accurate, complete, and reliable. You will build data quality checks, improve data pipelines, and work with data and business teams to deliver trusted data for reporting and analytics. Responsibilities Data Quality

• Design and implement data quality frameworks and standards.
• Build automated checks for data accuracy, completeness, and consistency.
• Create anomaly detection and data profiling solutions.
• Define and monitor data quality metrics and SLAs.
• Add validation checkpoints throughout the data lifecycle.

Data Governance & Compliance

• Maintain metadata, data dictionaries, and data lineage documentation.
• Ensure compliance with GDPR, CCPA, HIPAA, and other regulations.
• Implement security measures such as encryption, masking, and access controls.
• Support data governance policies and committees.

Collaboration & Leadership

• Work with data scientists, analytics engineers, and business teams.
• Mentor junior engineers and review code.
• Explain technical concepts to non-technical stakeholders.

Continuous Improvement

• Evaluate new tools and technologies for data quality and observability.
• Identify opportunities to improve processes and reduce technical debt.
• Lead proof-of-concept initiatives.

• Bachelor’s degree in Computer Science, Information Systems, or related field.
• 5+ years of experience in Data Quality Engineering, Data Governance, or Data Engineering.
• Experience implementing enterprise-level data quality solutions.
• Leadership experience and mentoring skills.

Technical Skills Programming & Data Engineering

• Strong SQL skills and query optimization.
• Python (Pandas, NumPy, PySpark).
• Apache Spark and Hadoop.
• Data modeling (Dimensional Modeling, Data Vault, 3NF).
• ETL/ELT development.

Cloud & Tools

• AWS, Google Cloud Platform, or Microsoft Azure.
• Snowflake, Amazon Redshift, or Google BigQuery.
• Data quality tools such as Great Expectations, Soda Core, or Monte Carlo.
• Workflow tools like Apache Airflow, Prefect, or Dagster.
• Data catalog tools such as DataHub, OpenMetadata, or Alation.
• Git and CI/CD.

Compliance Knowledge

• Understanding of GDPR and CCPA.
• Knowledge of data security and access controls.
• Experience with metadata and data lineage.

Looking forward to qualified local submissions only.

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