Description

You will build and maintain data quality systems across data pipelines.

This role is on-site.

Responsibilities

• Profile and assess data sources to identify anomalies, duplicates, and missing values.
• Design and implement automated data validation frameworks within ETL pipelines.
• Build reusable data quality rules and monitoring systems for real-time issue detection.
• Investigate data discrepancies to determine root causes and drive permanent resolutions with engineering teams.
• Ensure data handling meets regulatory standards, including implementing data masking and lineage tracking.

Required Skills

• Expert-level SQL for complex querying.
• Proficiency in Python for automation scripting.
• Hands-on experience with Snowflake, AWS, or Databricks.
• K knowledge of Spark, Hadoop, or Kafka for large-scale pipeline management.
• Proficiency in data visualization tools like Power BI or Tableau.
• Minimum of 5+ years of relevant experience in Data Engineering or ETL Testing.

Preferred Skills

• Experience with any Graduate education level.
• Familiarity with regulatory compliance frameworks.

Key Skills

Education

Any Graduate