Snowflake Data Engineer
Job in
Frankfort, Franklin County, Kentucky, 40601, USA
Listed on 2026-09-08
Listing for:
Propel London Ltd.
Full Time
position Listed on 2026-09-08
Job specializations:
-
IT/Tech
Data Engineering, Data Warehousing, Information Security & Data Protection
Job Description & How to Apply Below
Snowflake Data Engineer About the Role
We're looking for a Snowflake Data Engineer with solid hands-on experience to help build and maintain our cloud data warehouse and pipelines. You'll take ownership of moderately complex data engineering tasks, work closely with senior engineers on data architecture decisions, and partner with analysts and data scientists to deliver reliable, well-modeled data.
Key Responsibilities- Design, build, and maintain ETL/ELT pipelines feeding into Snowflake
- Develop and optimize Snowflake data models (star/snowflake schemas, staging/curated layers)
- Write efficient SQL and use Snowflake features such as Streams, Tasks, and Snowpipe for automation
- Manage data ingestion from various sources (APIs, files, databases) using tools like Fivetran, Airbyte, or custom scripts
- Implement transformation logic using dbt (data build tool) or similar frameworks
- Monitor and optimize warehouse performance, query efficiency, and credit/cost usage
- Implement data quality checks and basic monitoring/alerting for pipeline health
- Support role-based access control (RBAC), data governance, and security within Snowflake
- Participate in code reviews, follow CI/CD practices, and maintain version control via Git
- Troubleshoot pipeline failures and data quality issues, escalating complex problems as needed
- Document pipelines, data models, and processes for team and stakeholder reference
- Collaborate with analysts and data scientists to understand data requirements and deliver fit-for-purpose datasets
- 5-7 years of experience in data engineering, with at least 2-3 years working directly with Snowflake
- Strong SQL skills and experience with relational/cloud data warehouses
- Understanding of dimensional data modeling and ETL/ELT design principles
- Experience with at least one ELT/transformation tool (dbt preferred)
- Familiarity with a cloud platform (AWS, Azure, or GCP) that Snowflake runs on
- Experience with Git-based version control and basic CI/CD workflows
- Working knowledge of Python or another scripting language for automation
- Good communication skills and ability to work within a team, taking direction from senior engineers when needed
- Snow Pro Core Certification
- Experience with Snowflake-native features:
Streams, Tasks, Snowpipe, Time Travel, Zero-Copy Cloning - Familiarity with orchestration tools (Airflow, Dagster, or Snowflake Tasks)
- Exposure to data ingestion tools (Fivetran, Airbyte, Matillion)
- Basic understanding of streaming data concepts
- Post secondary diploma in Computer Science, Engineering, or related field (or equivalent practical experience)
We're looking for a Snowflake Data Engineer with solid hands-on experience to help build and maintain our cloud data warehouse and pipelines. You'll take ownership of moderately complex data engineering tasks, work closely with senior engineers on data architecture decisions, and partner with analysts and data scientists to deliver reliable, well-modeled data.
Key Responsibilities- Design, build, and maintain ETL/ELT pipelines feeding into Snowflake
- Develop and optimize Snowflake data models (star/snowflake schemas, staging/curated layers)
- Write efficient SQL and use Snowflake features such as Streams, Tasks, and Snowpipe for automation
- Manage data ingestion from various sources (APIs, files, databases) using tools like Fivetran, Airbyte, or custom scripts
- Implement transformation logic using dbt (data build tool) or similar frameworks
- Monitor and optimize warehouse performance, query efficiency, and credit/cost usage
- Implement data quality checks and basic monitoring/alerting for pipeline health
- Support role-based access control (RBAC), data governance, and security within Snowflake
- Participate in code reviews, follow CI/CD practices, and maintain version control via Git
- Troubleshoot pipeline failures and data quality issues, escalating complex problems as needed
- Document pipelines, data models, and processes for team and stakeholder reference
- Collaborate with analysts and data scientists to understand data requirements and deliver fit-for-purpose datasets
- 5-7 years of experience…
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