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Popular Databricks/PySpark data engineer role in Bangalore with broad tech requirements and recognizable employer, high applicant density.
Core PySpark/Databricks data engineering skills are broadly transferable across industries.
Explicit 2–4 years plus mandatory Databricks, PySpark, Python, and SQL requirements increase shortlisting strictness.
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Design, develop, and maintain scalable data pipelines and ETL/ELT workflows using Python and PySpark on Azure Databricks.
Manage Delta Lake implementations and configure Databricks clusters for optimized performance.
Collaborate with cross-functional teams to ensure data reliability, governance, and high-quality data warehousing solutions using cloud platforms.
2 to 4 years of experience in data engineering roles.
Strong hands-on experience with Python, PySpark, and Azure Databricks including Delta Lake and cluster management.
Proficiency in SQL and experience with data warehousing platforms such as Snowflake, Azure Synapse Analytics, or AWS Redshift.
Location requirement: Bangalore (Hybrid).
Experienced in designing efficient data pipelines and warehousing solutions with a focus on cloud-based environments, especially Azure.
Comfortable implementing DevOps practices such as CI/CD pipelines and containerization (Docker, Kubernetes) in data engineering workflows.
Familiar with orchestration tools like Apache Airflow and has knowledge of both structured and unstructured data processing.