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Strong employer brand, metro location and mid-level role, but niche Snowflake/Databricks skills moderate applicant density.
Core data engineering skills are transferable, but Snowflake/Databricks specialization moderately narrows cross-industry fit.
Explicit 4+ years plus mandatory Databricks and Snowflake hands-on requirements enforce strict technical filters.
Design, develop, and optimize large-scale data pipelines across Databricks and Snowflake platforms.
Develop PySpark applications and Snowflake ELT workflows focusing on scalability, performance, and cost efficiency.
Collaborate with data engineers, analysts, and business stakeholders to deliver compliant, high-quality cloud data solutions and provide debugging support.
Bachelor's degree in Computer Science, IT, or related field, or equivalent experience.
4+ years of experience in data engineering or big data development.
3+ years hands-on experience with Databricks, PySpark, Azure Data Engineering, Snowflake SQL, and ELT development.
Strong experience with performance tuning, data pipeline development using Databricks, Snowflake, and Azure Data Factory or Synapse.
Demonstrated expertise in managing integrated cloud data pipelines using Databricks and Snowflake in Azure environments.
Strong proficiency in PySpark, Snowflake SQL, and related orchestration tools ensuring scalable and cost-optimized solutions.
Experience working closely with business stakeholders and cross-functional teams in agile settings to translate requirements into technical implementations.