We’re seeking talented data engineers excited to scale their knowledge of data pipelining, cloud warehouse management, and query performance to hundreds of companies. As a data engineer in a product organization, you will be tasked with understanding our customers’ needs, working closely with the broader engineering team, and developing data pipelines that will be deployed as part of the core Preql engine.
What we're looking for
- You have strong opinions about moving data between systems, love optimizing pipelines and warehouse performance, and are excited to experiment with new technologies in order to solve problems
- You’re a skilled collaborator, excited about partnering with folks on the product, design and software engineering side of the business
- You love tackling complex problems and getting creative when developing solutions
- Experience in Python (or another scripting language), experience working in cloud environments and cloud data warehouses. Experience with streaming data systems is a plus
Responsibilities
- Own the architecture and development of data pipelines between the Preql software, our backend systems, and customer data stores
- Collaborate with software engineers, product managers, designers, and analysts
- Speak directly with customers alongside team members to understand and deliver solutions
- Balance speed and quality, with a focus on tangible results
- Share knowledge, promote best practices and collaborate with fellow engineers
- Bind our services together while delivering testable, maintainable, and high-quality code
Qualifications
- 3-5 years experience as a data engineer or analytics engineer
- Advanced expertise in SQL, SQL optimization techniques working with cloud-based storage solutions (Snowflake, BigQuery, Redshift) and data ingestion tools (Fivetran, Stitch)
- Experience with data pipeline management technologies with dependency checking (Airflow, dbt), schema design, and dimensional data modeling
- Ability to leverage tools, business intuition, and attention to detail for data validation and QA
- Excellent communication skills, particularly when explaining technical or complex matters to less technical co-workers
- Flexible and focused on solutions
- Organized and self-sufficient