Databricks

Job Summary:
We are seeking a highly skilled Senior Databricks Engineer to join our data team. The ideal candidate will have strong expertise in Python programming, ETL processes, and in-depth knowledge of Medallion Architecture in modern Data Lakehouse environments. You will play a key role in designing, developing, and optimizing scalable data pipelines and analytics solutions on the Databricks platform. ________________________________________ Key Responsibilities: Design, develop, and maintain robust ETL pipelines using Databricks and Python. Implement and optimize the Medallion Architecture (Bronze, Silver, Gold layers) within our Data Lakehouse ecosystem. Collaborate with data engineers, data scientists, and business stakeholders to translate business requirements into scalable data solutions. Perform data ingestion, transformation, cleansing, and enrichment from various structured and unstructured data sources. Optimize Spark jobs for performance and cost-efficiency on Databricks. Implement best practices for data governance, security, and quality within the data pipelines. Mentor junior team members and contribute to improving team processes and standards. Troubleshoot and resolve data pipeline and platform-related issues promptly. ________________________________________ Required Skills & Qualifications: 10+ years of experience in data engineering or a related field. Strong proficiency in Python programming and libraries related to data processing (PySpark preferred). Hands-on experience with Databricks platform and Apache Spark. Deep understanding of ETL concepts and implementation in large-scale data environments. Expertise in Medallion Architecture and Data Lakehouse design patterns. Experience with data storage technologies like Delta Lake, Parquet, and cloud data platforms (AWS, Azure, or GCP). Familiarity with SQL and performance tuning of Spark SQL queries. Strong problem-solving skills and attention to detail. Excellent communication and collaboration skills. ________________________________________ Preferred Qualifications: Experience with containerization (Docker/Kubernetes) and orchestration tools (Airflow, Azure Data Factory). Knowledge of CI/CD pipelines for data workflows. Exposure to machine learning pipelines and MLOps. .