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Reputable finance employer, Bangalore metro, and popular Databricks/Spark stack create moderate candidate competition.
Cloud Databricks/Spark skills transfer broadly, but finance-preference raises background sensitivity.
Explicit 8–11 years and mandatory Databricks/AWS/Spark/SQL skills make shortlisting highly strict.
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Lead design and delivery of scalable cloud data platforms using Databricks on AWS, focusing on ETL/ELT pipelines, data warehousing, and Lakehouse architecture.
Define and govern cloud data architecture standards ensuring data quality, performance, security, and platform reliability.
Provide technical leadership and mentor engineering teams, driving cloud modernization and CI/CD automation best practices.
8–11 years of experience in Data Engineering, Data Architecture, or related roles.
Proven expertise in AWS, Databricks, Python, Apache Spark, SQL, and data modeling with cloud data platform implementation experience.
Experience leading solution design, architecture discussions, and technical delivery.
Work Experience Required: 8-11 years; Financial Services or Asset Management experience preferred but not mandatory.
Experienced technical leader capable of governing architecture and mentoring engineering teams in cloud data solutions.
Strong background in scalable data platform design, specifically with Databricks on AWS and Lakehouse architectures.
Capable of driving modernization initiatives including automation and CI/CD in a data engineering context within financial services or asset management environments.