3-5 years' experience
Must have experience with Databricks, PowerBI and SQL.
Need to build your own PowerBI Reports.
Key Responsibilities
• Design and implement enterprise data quality frameworks and controls.
• Develop automated validation, monitoring, and exception reporting solutions.
• Measure and improve data quality across Accuracy, Completeness, Consistency, Validity, Integrity, Uniqueness, and Timeliness.
• Partner with Data Governance teams to operationalize data quality standards.
• Investigate and resolve complex data quality issues through root cause analysis.
Data Engineering
• Build and optimize ETL/ELT pipelines using Databricks, Python, SQL.
• Embed data quality validations into ingestion and transformation processes.
• Develop reusable validation components and automated testing frameworks.
• Support cloud data platforms and modernization initiatives.
DevOps & Collaboration
• Build and maintain CI/CD pipelines and Git-based deployment processes.
• Collaborate with engineers, architects, analysts, and business stakeholders.
• Translate business requirements into scalable technical solutions.
• Present findings and recommendations to technical and business audiences.
Required Qualifications
• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.
• 5+ years of experience in Data Engineering, Data Quality Engineering, or related roles.
• Strong expertise in:
o SQL
o Python
o Databricks & Spark
o Oracle and modern cloud data platforms
o Git and CI/CD pipelines
• Strong analytical, troubleshooting, and root cause analysis skills.
• Excellent communication and stakeholder management abilities.