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Tier-1 brand, popular Data Engineer role, 3–6 year band, metro location.
Data engineering skills (PySpark, Databricks, Power BI) are broadly transferable across industries.
Explicit 3–6 year requirement plus mandatory Databricks, PySpark, Azure and Power BI skills.
Develop and maintain ETL/ELT data pipelines using Databricks with Python and PySpark for large-scale data processing.
Design, build, and deploy data models, transformations, CI/CD pipelines, and reusable data engineering frameworks to ensure data quality, reliability, and performance.
Create and integrate Power BI dashboards and reports using DAX expressions and Power Query; collaborate with reliability engineers on Power BI visualizations.
Bachelor’s or Master’s degree in Electronics, Electrical Engineering, or Computer Science Engineering.
2 to 5 years of experience in data engineering, including building and maintaining data pipelines using Databricks.
Proficiency in Python, PySpark, Microsoft Power BI (including DAX and Power Query), and familiarity with Azure Cloud data engineering tools.
Work Experience Required: 2 to 5 years
Experienced in end-to-end data engineering supporting analytics and reporting workflows in an enterprise environment.
Comfortable working with cross-functional international teams and integrating data engineering outputs into business applications.
Familiar with automation, CI/CD pipelines, and ensuring data pipeline quality and performance in cloud-based platforms, preferably Azure.