Senior Snowflake Data Engineer, ETL & Python
Overview
You will own the design, build, and optimization of enterprise-scale data pipelines on Snowflake, processing billions of rows daily. You will join a tight-knit data engineering team of 6 at JBS Technologies, collaborating with data scientists and analysts to power real-time analytics. Your work will directly shape the company's data strategy in the cloud. This role stands out for its focus on Snowflake performance tuning and the chance to mentor junior engineers.
What You'll Do10
- 1Design and implement Snowflake schemas, tables, and views to support analytical workloads.
- 2Build and maintain automated data pipelines using Azure Data Factory and Airflow.
- 3Develop and optimize Snowflake SQL queries, tasks, and streams for sub-second performance.
- 4Implement role-based access control (RBAC) and clustering keys to ensure data security and speed.
- 5Write Python scripts to orchestrate data transformations and integrate with APIs.
- 6Monitor and debug pipeline failures, ensuring data accuracy and 99.9% uptime.
- 7Collaborate with data analysts to refine ETL/ELT processes based on evolving business needs.
- 8Lead code reviews and enforce best practices for Snowflake data modeling.
- 9Automate routine maintenance tasks such as warehouse scaling and resource monitors.
- 10Document data flow architectures and maintain a data catalog for team-wide clarity.
Requirements6
- 15+ years of hands-on experience with Snowflake, including SQL, Tasks, Streams, Warehouses, and RBAC.
- 2Proven ability to tune Snowflake performance: clustering, pruning, and query profiling.
- 3Strong Python skills for data engineering: writing efficient scripts for ETL/ELT.
- 4Experience building and orchestrating pipelines with Azure Data Factory and/or Airflow.
- 5Solid understanding of ETL/ELT frameworks and data pipeline design principles.
- 6Excellent communication and collaboration skills for cross-functional teamwork.
Salary Insight
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