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Metro Bangalore, mid-level generalist data-engineer title and broad skill requirements increase applicant competition.
Snowflake and DBT expertise is domain-specific but transferable across analytics-heavy industries, indicating medium sensitivity.
Explicit 4–12 years plus mandatory Snowflake, DBT, ETL and Python skills enforce high shortlisting strictness.
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Own the development and optimization of complex SQL scripts, stored procedures, and data transformations within Snowflake to support data warehousing and analytics.
Collaborate closely with data analysts, architects, and business teams to deliver reliable data solutions that meet business requirements.
Monitor, troubleshoot, and ensure performance, data quality, and compliance standards in Snowflake-based data pipelines and associated tools.
4 to 12 years of relevant experience in data engineering or related roles.
In-depth knowledge and hands-on experience with Snowflake's data warehousing capabilities and optimization.
Strong expertise in SQL (queries, stored procedures, user-defined functions) and Python programming.
Experience with ETL/ELT tools such as Snowpipe, AWS Glue, openflow, or Fivetran, DBT for database modeling, and version control tools like Azure DevOps.
Experienced in implementing and optimizing dimensional data models (star/snowflake schemas) for analytics and reporting.
Operationally focused on performance tuning and cost optimization within cloud data warehouse environments, especially Snowflake.
Skilled in end-to-end data solution delivery with proficiency in both integration of diverse data sources and governance/compliance adherence.