Job
Description
Role & responsibilities 3-6 years of experience in Data Engineering Pipeline Ownership and Quality Assurance, with hands-on expertise in building, testing, and maintaining data pipelines. Proficiency with Azure Data Factory (ADF), Azure Databricks (ADB), and PySpark for data pipeline orchestration and processing large-scale datasets. Strong experience in writing SQL queries and performing data validation, data profiling, and schema checks. Experience with big data validation, including schema enforcement, data integrity checks, and automated anomaly detection. Ability to design, develop, and implement automated test cases to monitor and improve data pipeline efficiency. Deep understanding of Medallion Architecture (Raw, Bronze, Silver, Gold) for structured data flow management. Hands-on experience with Apache Airflow for scheduling, monitoring, and managing workflows. Strong knowledge of Python for developing data quality scripts, test automation, and ETL validations. Familiarity with CI/CD pipelines for deploying and automating data engineering workflows. Solid data governance and data security practices within the Azure ecosystem. Additional Requirements: Ownership of data pipelines ensuring end-to-end execution, monitoring, and troubleshooting failures proactively. Strong stakeholder management skills, including follow-ups with business teams across multiple regions to gather requirements, address issues, and optimize processes. Time flexibility to align with global teams for efficient communication and collaboration. Excellent problem-solving skills with the ability to simulate and test edge cases in data processing environments. Strong communication skills to document and articulate pipeline issues, troubleshooting steps, and solutions effectively. Experience with Unity Catalog or willingness to learn. Preferred candidate profile Immediate Joiner's
