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Tier-1 brand, mid-level Databricks data engineer role and Gurgaon metro location increase applicant competition.
Databricks and data engineering skills are transferable, but Lakehouse and consulting specifics boost domain sensitivity.
Explicit 5–8 years plus mandatory Databricks, Spark, Delta Lake and cloud experience makes screening highly strict.
Design, build, and maintain scalable data pipelines using Databricks Lakehouse Platform including PySpark, Spark SQL, and Delta Lake.
Optimize Spark jobs for performance and cost efficiency while ensuring data quality, lineage, and governance.
Collaborate with analytics, AI/ML, and business teams; provide production support and mentor junior engineers.
5 to 8 years of experience as Data Engineer with Databricks expertise.
Strong hands-on skills in Apache Spark, PySpark, Spark SQL, and Delta Lake architecture.
Proficient in SQL, ETL/ELT patterns, data warehousing concepts, and exposure to at least one cloud platform (Azure, AWS, or GCP).
Bachelor's or Master's degree in Computer Science, Engineering, or related field with 60% and above.
Experienced in Agile team environments with a strong focus on distributed computing and cloud-native data engineering.
Skilled in collaborating across functions with data scientists and analysts to support AI/ML workloads and data governance.
Capable of production-level pipeline maintenance and mentoring, with potential certification in Databricks as a plus.