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Strong employer brand, Bangalore location, mid-level generalist data role with broad technical requirements increases candidate competition.
Core data engineering skills transfer well across industries, though Snowflake/dbt/platform experience adds moderate domain specificity.
Explicit 5+ years, required lead experience, and specific data platform and tech mandates increase shortlisting strictness.
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Lead and manage a data engineering team, overseeing project architecture, sprint planning, and day-to-day operations.
Own design and delivery of enterprise-scale data pipelines and analytics platforms collaborating with business stakeholders to meet data needs.
Contribute to shared data engineering frameworks, onboarding programs, platform stability via DevOps, and implement data quality and operational SLAs.
Bachelor's degree or higher in Computer Science, Statistics, Business, IT, or related field.
5+ years of experience in data engineering including 2+ years in a technical lead or team lead role.
Proficiency in Python (OOP, reusable libraries), advanced SQL (window functions, optimization), cloud DevOps including CI/CD, and Agile methodology experience.
Experience with enterprise data engineering, modern tooling such as Dagster, dbt, Snowflake, data quality frameworks, and platform shared services.
Experienced leader with capability to own end-to-end data engineering architecture and lead cross-functional delivery teams.
Strong technical expertise in cloud-based data platforms, pipeline architecture, and operational stability with DevOps focus.
Strategic thinker able to communicate technical concepts to business, contribute to organizational frameworks, and drive continuous improvement and team growth.