Position Summary
We are looking for a highly skilled Senior Data Engineer to design build and optimize scalable data solutions in a hybrid work environment. The ideal candidate will have strong expertise in Python and Snowflake with a focus on pipeline automation data security performance optimization and analytics support.
Key Responsibilities
- Design build and maintain scalable batch and real-time data pipelines using Python SQL and Snowflake
- Develop and manage Snowflake data warehouses and lakes to support business analytics
- Implement security features such as row-level access and dynamic masking for sensitive data
- Monitor Snowflake query performance warehouse usage and credit consumption for cost efficiency
- Collaborate with data science and analytics teams to support machine learning and analytical initiatives
- Create semantic layers and dimensional data models (Star/Snowflake schemas) for BI tools
- Automate workflows using CI/CD pipelines (e.g. Jenkins GitHub) and orchestration tools (e.g. Airflow dbt)
- Facilitate secure external data sharing through Snowflake shares and reader accounts
Required Technical Skills
- Strong Python skills for ETL scripting automation and data transformation
- Deep knowledge of Snowflake architecture security policies (RBAC masking) and performance tuning
- Advanced SQL skills for writing optimizing and debugging complex queries
- Hands-on experience with data orchestration and ETL tools such as Airflow dbt or Informatica
Preferred Skills
- Experience integrating with ML/AI/LLM models
- Familiarity with data observability tools such as Great Expectations
- Exposure to metadata management platforms like DataHub or Collibra
Soft Skills
- Excellent communication and collaboration skills
- Strong problem-solving abilities with a focus on data quality and pipeline scalability
Work Model
- Hybrid work arrangement: 3 to 4 days onsite per week in Houston TX