
Data Engineer
Snowflake · Posted Oct 28
Cloud data warehousing, analytics, data sharing, and AI infrastructure services
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About the role
Snowflake's Data Engineer role sits within a team building and operating the data pipelines and models that power internal decision-making on the Snowflake AI Data Cloud. The work spans ingestion, transformation, and consumption using Snowflake, dbt, and Apache Airflow, with an emphasis on data quality, cost, and performance monitoring. The engineer also acts as an internal customer zero, feeding back on Snowflake features with Product teams while growing ownership of production data products.
What you will do
- Build and maintain production data pipelines and models on Snowflake, from ingestion through transformation and consumption
- Develop dbt models with tests and documentation that follow team standards and governance practices
- Build and support Apache Airflow DAGs that orchestrate Snowflake workloads reliably
- Ingest data from enterprise sources using Snowpipe, Snowpark, and dynamic tables
- Apply data quality checks and help monitor Snowflake warehouse cost and performance
- Act as an internal customer zero, sharing feedback on Snowflake features with Product teams
- Take part in Agile ceremonies including stand ups, sprint planning, reviews, and retrospectives
- Partner with stakeholders and senior engineers to turn well-defined requirements into scoped technical tasks
Skills used in this role
What the employer is looking for
- Bachelor's degree in Computer Science, Information Systems, or a related field, or equivalent practical experience
- 3+ years of hands-on experience building data pipelines or data models in a production environment
- Strong SQL and working Python skills, including basic query tuning and schema design
- Hands-on experience with a cloud data warehouse, ideally Snowflake
- Working knowledge of dbt and an orchestration tool such as Apache Airflow
- Understanding of dimensional modelling concepts
- Clear written and verbal communication and a collaborative, curious approach to learning
- Ownership mindset: you follow problems through to resolution and ask for help when needed
Preferred qualifications
- Exposure to Snowflake Cortex AI functions or other LLM APIs for data enrichment
- Experience preparing data for ML model training or feature engineering
- Familiarity with streaming ingestion such as Kafka or Snowpipe Streaming
- Experience with AWS, Azure, or GCP, including infrastructure-as-code
- Awareness of data contracts or schema registry tooling
Benefits and support
- Compensation and benefits are detailed in the job posting
About Snowflake
Snowflake delivers the AI Data Cloud, a cloud-based platform that unifies data warehousing, data lakes, data engineering, and data sharing. Its architecture separates compute from storage, enabling organizations to securely store, govern, and analyze data across multiple public clouds. The platform also integrates generative AI services and developer frameworks to help enterprises scale advanced workloads.
- Industry
- Cloud Computing
- Company size
- 10001+ employees
- Founded
- 2012-07-23
- Location
- Bozeman, Montana, USA
- Funding stage
- Public Company
Funding
Public Company · $1.56B raised
- 2012-02-01Seed$900K
- 2012-08-01Series A$5M
- 2014-10-01Series B$26M
- 2015-06-01Series C$79M
- 2017-09-01Series D$105M
- 2018-01-01Series E$263M
- 2018-10-01Series F$450M
- 2020-02-01Series G$479M
- 2020-09-16Post IPO$376M
Leadership
Chief Executive Officer
Chief Financial Officer
Executive Vice President, Product
Chief Technology Officer
Chief Security and Trust Officer
Recent coverage
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