IN_Senior Associate_Data Engineer Databricks_GCC_Advisory_Gurgaon
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Protocol Intelligence
Data-driven signals on your job's competitivenessTier-1 brand, metro location, and mid-level experience suggest moderate candidate density despite Databricks specialization.
Databricks and Delta Lake specialization increases domain specificity, but core data engineering skills are transferable.
Explicit 3–8 years plus mandatory Databricks, Spark, Delta Lake and cloud experience enforces stringent filters.
Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and maintain scalable, high-performance data pipelines on Databricks Lakehouse Platform using PySpark, Spark SQL, and Delta Lake.
Optimize data processing workflows and support analytics, reporting, AI/ML workloads by collaborating with cross-functional teams.
Ensure data quality, governance, security compliance, provide production support, troubleshoot pipelines, and document technical solutions.
Minimum Requirements
3+ years of experience as a Data Engineer with strong Databricks expertise.
Bachelor's or Master's degree in Computer Science, Engineering, or related field with minimum 60% marks.
Hands-on experience with Apache Spark, PySpark, Spark SQL, Delta Lake, data warehousing, ETL/ELT patterns, and at least one cloud platform (Azure/AWS/GCP).
Work Experience Required: 3 to 8 years. Notice period: Not explicitly mentioned in the JD.
Ideal Candidate Profile
Experienced in building and optimizing data pipelines in Databricks environment with strong command over distributed computing concepts.
Familiarity with Agile team workflows and ability to collaborate effectively with data scientists, analysts, and architects on AI/ML workloads.
Knowledge or certification in Databricks, data governance tools like Unity Catalog, streaming frameworks, and CI/CD for data pipelines is a plus.