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Tier-1 brand, mid-level Data Engineer title, metro location, and common required skills increase competition.
Data engineering skills are transferable across industries, but Azure/Databricks platform experience increases role specificity.
Explicit 4-8 years plus mandatory Databricks, PySpark, and Azure experience increases screening strictness.
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Design, build, and optimize scalable data pipelines using Databricks, Azure Data Factory, Microsoft Fabric, and PySpark.
Architect and implement data lakehouse and data warehouse solutions on Databricks/Microsoft Fabric.
Develop ETL/ELT workflows and maintain production data pipelines with focus on performance, reliability, and data quality.
4-8 years of experience in data engineering, specifically with cloud data platforms.
Proficiency in PySpark, Azure Data Factory, Databricks, Microsoft Fabric, and SQL.
Bachelor's or master's degree in Computer Science, Information Systems, Engineering, or related field.
Primary work location Bangalore, India; shift: Shift 1 (India).
Experienced in implementing scalable data architectures (lakehouse and warehouse) using Microsoft Fabric and Azure analytics services.
Hands-on with CI/CD pipelines, infrastructure-as-code, deployment automation, and collaboration with cross-functional technical teams.
Strong in complex SQL development, data modeling, and enabling data readiness for data scientists and analysts.