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Popular data-role, Bangalore metro, and broad cloud/Databricks skillset increase candidate density.
Core data engineering skills are transferable across industries despite cloud-specific tools.
Requires 2+ years plus specific Databricks/BigQuery/cloud skills, making shortlisting moderately strict.
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Build and maintain scalable data pipelines using cloud platforms like GCP, Azure, or AWS, with focus on Databricks, BigQuery, and cloud storage.
Develop data processing and transformation workflows using Python, SQL, Spark/PySpark, supporting batch and near real-time ingestion.
Ensure reliability of data pipelines through monitoring, validation, and quality checks, and prepare datasets for BI and analytics teams.
2+ years of hands-on experience in Data Engineering.
Proficient with at least one major cloud platform (GCP, Azure, or AWS), including experience with Databricks and BigQuery or similar cloud storage technologies.
Skilled in Python, SQL, Spark/PySpark, and ETL/ELT development with data warehousing knowledge.
Familiarity with Airflow or Cloud Composer; Work Experience Required: 2+ years.
Experience working in cloud-centric environments with modern data platforms and tools like Databricks and BigQuery.
Operates independently with strong ownership of data engineering tasks and clear communication within technical teams.
Comfortable handling both batch and streaming data ingestion and transformations using cloud-native services and orchestration tools.