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Tier-1 brand, mid-level data engineer title, metro location and broad Databricks/PySpark skills increase candidate competition.
Core PySpark, Databricks and Azure data engineering skills are highly transferable across industries.
Explicit 3-6 years and mandatory Databricks, PySpark, Azure and Power BI skills enforce strict shortlisting filters.
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Develop and maintain ETL/ELT data pipelines using Databricks, focusing on large-scale data processing with PySpark and Python.
Design, deploy, and optimize Power BI reports, including data modeling, DAX expressions, Power Queries, and integration into applications.
Build reusable data engineering frameworks, ensure data quality, reliability, and support downstream analytics and reliability teams.
Bachelor’s or Master’s degree in Electronics, Electrical Engineering, or Computer Science Engineering.
2 to 5 years of hands-on experience in data engineering, specifically with Databricks and ETL/ELT workflows.
Proficiency in Python, PySpark, and Microsoft Power BI (including DAX and Power Query).
Familiarity with Azure cloud data engineering tools.
Experience working with large-scale data processing and automation in data engineering projects.
Strong skills in creating and optimizing data visualizations and dashboards using Power BI for business analytics.
Comfortable working in international, diverse teams with proactive communication and collaboration on technical discussions.