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Tier-1 brand, metro Bengaluru location, popular mid-senior data engineering role with broad skillset increases competition.
Technical data skills are transferable, but VP finance environment favors candidates with financial domain experience.
Mandatory 8+ years and required Snowflake Cortex and specific tech stack enforce high shortlisting strictness.
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Lead design, development, and maintenance of data infrastructure and ETL processes for Data AI platforms using Snowflake and related technologies.
Optimize data systems for performance and scalability while implementing data quality and governance standards.
Collaborate with cross-functional teams to translate business data needs into technical solutions and contribute to team knowledge sharing and technical documentation.
Minimum 8+ years of practical experience in data engineering or related field; typically at least 6 years relevant experience expected.
Proficiency in Python programming and experience with Snowflake, including mandatory expertise in Snowflake Cortex.
Experience with data processing frameworks (e.g., Apache Spark, Hadoop), database systems (SQL and NoSQL), and cloud platforms such as AWS or Azure.
Mandatory experience with ETL development, data modeling, data warehousing concepts, message queues/streaming (Kafka), and version control systems (Git).
Senior-level data engineer comfortable leading technical design and development of scalable data infrastructure in a financial services or large enterprise environment.
Experienced with modern data platforms including Snowflake, Databricks, and cloud-native data services, with strong hands-on skills in data architecture and ETL.
Able to work collaboratively across distributed teams and translate complex business data requirements into practical, efficient technical implementations.