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Tier-1 brand, generic Data Engineer title, mid-level experience band, and Bangalore metro increase competition.
Core data engineering skills are transferable across industries, though finance experience is preferred.
Explicit 3-7 years plus mandatory Databricks, Spark, Python, and cloud requirements make shortlisting highly strict.
Develop, maintain, and support batch and streaming data pipelines using PySpark, Spark SQL, and Databricks.
Implement Bronze/Silver/Gold architecture patterns for data processing solutions including incremental processing and Change Data Capture.
Participate in design, testing, deployment, and operational support of scalable data pipelines and products in cloud environments.
3-7 years experience in software engineering, data engineering, or related technical roles.
Bachelor's degree in Computer Science, Engineering, Information Systems, or related field (or equivalent experience).
Hands-on experience with Databricks including notebooks, workflows, and clusters.
Proficiency in Python (PySpark), SQL, and experience building production data pipelines in cloud platforms (Azure/AWS).
Experienced with distributed data processing and cloud-based data platform development and support.
Familiar with data lakehouse architectures and orchestration tools such as Airflow, Databricks Workflows, or Azure Data Factory.
Capable of troubleshooting and optimizing performance of data pipelines while supporting governance and data quality initiatives.