Back
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Tier-1 brand, Bangalore metro location, and popular data engineering role with broad cloud+Spark requirements.
Databricks/Spark/Azure specialization favors platform-experienced data engineers; moderately transferable across industries.
Explicit 10+ years requirement plus mandatory Databricks/Spark/Scala expertise creates strict technical shortlisting.
Design, develop, and maintain scalable data pipelines using Databricks, Apache Spark, and Scala for large-scale data processing.
Optimize Spark jobs and cluster utilization for performance, scalability, and reliability in production environments.
Collaborate with cross-functional teams to design data architectures, implement ETL frameworks, and support production incidents.
10+ years of experience in Data Engineering with 6+ years hands-on experience in Databricks and Spark development.
Strong expertise in Databricks, Apache Spark, Scala, Spark SQL, PySpark, and proficiency in SQL development and query optimization.
Experience in distributed data processing frameworks, ETL/ELT pipeline development, and cloud-native solutions on Microsoft Azure (including ADLS and ADF).
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
Proven ability to deliver production-grade scalable data engineering solutions with strong focus on Spark job performance and cluster optimization.
Experienced in managing Databricks workflows, job orchestration, and CI/CD pipelines within Agile environments.
Familiarity with financial services or reference data domains and additional skills such as Delta Lake, Unity Catalog, Snowflake, and Azure certification are advantageous.