
Lead Data Engineer
18 hours ago
The Role:
- We seek an experienced Senior Data Engineer to lead our data engineering team.
Key Responsibilities:
- Design and implement modular, test-driven ELT pipelines using dbt on Snowflake.
- Create layered data models (staging, intermediate, mart layers) aligned with dbt best practices.
- Oversee the ingestion of structured and semi-structured data from APIs, flat files, cloud storage into Snowflake.
- Optimize Snowflake for performance and cost through warehouse sizing, clustering, materializations, query profiling, and credit monitoring.
- Apply advanced dbt capabilities including macros, packages, custom tests, sources, exposures, and documentation.
- Orchestrate workflows using dbt Cloud, Airflow, or Azure Data Factory integrated with CI/CD pipelines.
- Define and enforce data governance and compliance practices using Snowflake RBAC, secure data sharing, and encryption strategies.
- Collaborate with analysts, data scientists, architects, and stakeholders to deliver validated business-ready data assets.
Requirements:
- Bachelor's or master's degree in computer science, Data Engineering, or a related field.
- Certifications such as SnowPro Advanced, dbt Certified Developer are beneficial.
Experience:
- 5 to 8 years of experience in data engineering roles with 3+ years of hands-on experience working with Snowflake and dbt.
Technical Skills:
- Expert-level knowledge of SQL and Snowflake including performance optimization, storage layers, query profiling, clustering, and cost management.
- Experience in dbt development: modular model design, macros, tests, documentation, and version control using Git.
Benefits:
- Opportunity to work on cutting-edge technologies.
- Collaborative and dynamic work environment.
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