Job Requirements
Job Summary:

We are looking for a highly motivated Data Quality Engineer to join our data engineering team. The ideal candidate will be responsible for building and maintaining robust data quality frameworks to ensure the accuracy, consistency, and reliability of data across platforms. You will collaborate with cross-functional teams to embed quality checks into data pipelines and support data-driven decision-making.

Key Responsibilities:Design and implement automated data quality checks and validation frameworks.  Perform data profiling, anomaly detection, and root cause analysis using Python and SQL.  Integrate data quality processes into ETL/ELT pipelines using PySpark and Databricks.  Monitor and resolve data quality issues across Azure/AWS-based data platforms.  Develop CI/CD pipelines for data quality automation using Git and DevOps tools.  Work with JDBC connectors to validate data movement and integrity across systems.  Document data quality rules, processes, and findings for technical and business stakeholders.Required Technical Skills:Programming Languages: Python, SQL  Big Data Tools: PySpark, Databricks  Cloud Platforms: Azure/AWS (e.g., S3, Lambda)  Data Connectivity: JDBC  Version Control: Git  DevOps/CI/CD Tools: Jenkins, GitHub Actions, Airflow  Visualization: PowerBISoft Skills:Agile Experience: Proven experience working in Agile development environments  Analytical Thinking: Strong analytical and problem-solving abilities  Critical Thinking: Ability to evaluate data issues logically and propose effective, scalable solutions  Communication: Excellent communication skills for cross-team collaboration and stakeholder engagementPreferred Qualifications:Experience with data governance and metadata management tools  Familiarity with data cataloging solutions  Understanding of data privacy compliance standards