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Tier-1 brand, metro location, mid-level generalist data engineer with broad skillset.
Core data engineering skills are broadly transferable, though industrial validation knowledge slightly favours manufacturing domain.
Explicit 2–5 years plus Databricks, PySpark, Power BI and Azure mandates narrow technical fit.
Develop and maintain ETL/ELT pipelines using Databricks and write efficient PySpark and Python scripts for large-scale data processing.
Design and deploy data models, transformations, CI/CD pipelines, and Power BI dashboards including DAX and Power Query for analytics and reporting.
Ensure data quality, reliability, and performance across pipelines and collaborate with teams to integrate Power BI reports into applications and support downstream consumers like analytics and testing teams.
Bachelor's or Master's degree in Electronics, Electrical Engineering, or Computer Science Engineering.
2 to 5 years of work experience in data engineering, specifically with hands-on experience in Databricks and building data pipeline solutions.
Proficiency in Python, PySpark, and Microsoft Power BI including DAX expressions and Power Query.
Familiarity with Azure Cloud Data Engineering Tools.
Experienced in end-to-end data pipeline development and automation with a strong focus on data quality and performance.
Skilled in building actionable dashboards and integrating data visualization within business applications using Microsoft Power BI.
Capable of working in international, diverse teams and open to technical discussions, reviews, and assessments.