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Strong employer brand, metro location, and a popular mid-level data engineer profile increase applicant competition.
Core data engineering skills (PySpark, Databricks, ETL, Power BI) are broadly transferable across industries.
Explicit 2-5 years plus mandatory Databricks, PySpark, Power BI and Azure skills raise shortlisting strictness.
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Develop and maintain ETL/ELT pipelines using Databricks and implement data models, transformations, and CI/CD pipelines for automation.
Design, build, and optimize Power BI data models and dashboards, including writing DAX expressions and Power Queries, and integrate reports into applications.
Support downstream teams such as analytics, reporting, testing, and reliability by ensuring data quality, reliability, and performance across pipelines and frameworks.
2 to 5 years of experience in data engineering with hands-on experience building and maintaining data pipeline solutions using Databricks.
Bachelor’s or Master’s degree in Electronics, Electrical Engineering, or Computer Science Engineering.
Proficiency in Python and PySpark programming for large-scale data processing.
Knowledge of Microsoft Power BI including DAX expressions, Power Query, and familiarity with Azure Cloud Data Engineering tools.
Experienced in large-scale data processing and automation within ETL/ELT workflows using Databricks and related tools.
Skilled at developing advanced data visualizations and reports on Power BI with integration into applications.
Comfortable working with international teams and supporting analytics, testing, and reliability functions across diverse use cases.