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Metro, mid-level role with hybrid work and generalist data skills, though Snowflake specialization reduces competition.
Data engineering skills (SQL, ETL, Snowflake) are broadly transferable across industries.
Mandatory 4+ years plus Snowflake/ETL skills, moderate technical filters without required certifications.
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Own development and maintenance of Snowflake database objects including SQL scripts, views, stored procedures, and data transformation workflows.
Develop and support ETL/ELT pipelines for loading and transforming structured and semi-structured data in Snowflake with focus on performance optimization and compliance with coding standards.
Provide production support by monitoring data workflows, resolving incidents within SLAs, and ensuring quality through testing and collaboration with cross-functional teams.
Minimum 4 years of related experience in software development or data engineering.
Bachelor's degree preferred or equivalent experience.
Strong knowledge of SQL, data warehousing principles, and Snowflake development basics.
Not explicitly mentioned in the JD: Notice period, mandatory programming languages beyond basic knowledge, specific certifications, or location restrictions.
Experience working with Snowflake architecture and development features such as Streams, Tasks, Snowpark, or Snowpipe is a strong advantage.
Comfortable in Agile development environments, collaborating with product owners, QA, and senior developers.
Technical proficiency with ETL/ELT processes, database optimization, and familiarity with cloud platforms like AWS, Azure, or GCP increases competitiveness.