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Popular mid-level data-engineer role with broad cloud/Databricks requirements and 5-year filter increases competition.
Core data engineering skills are highly transferable across industries despite preferred education/government experience.
Explicit five-year minimum plus mandatory Databricks, AWS, Spark, and SQL skills create strict shortlisting filters.
Design, build, and maintain scalable ETL pipelines and core data infrastructure to power BI and ML initiatives.
Optimize data warehouses, lakes, and queries for performance, cost, and reliability.
Implement data quality checks, security protocols, and collaborate with data scientists and analysts to deliver clean, analysis-ready datasets.
Bachelor's or Master's degree in CS, IT, EC, Data Engineering, or related technical field (or equivalent experience).
Strong proficiency in Python and expert-level SQL skills.
Experience with relational databases (PostgreSQL, MySQL, SQL Server), AWS cloud services, Databricks, and ETL workflow automation tools (AWS Lambda, Step Functions, Airflow).
Minimum 5 years of relevant work experience.
Has experience working on education or eGovernance projects related to State or Central government programs.
Possesses strong troubleshooting and analytical skills for complex data bottlenecks in large-scale data environments.
Expertise operating within AWS and Databricks ecosystems with knowledge of big data frameworks (e.g., Apache Spark) and workflow orchestration.