Fivetran is building data pipelines to power the modern data stack for thousands of companies. We’re looking for a data engineer to join our Growth team – a startup within Fivetran! As the primary data engineer on Growth, you’ll be able to operate with autonomy and create tremendous impact.
You’ll collaborate with product, engineering, data science, data analytics, sales and marketing to create an operational analytics environment that powers Fivetran’s product-led growth strategy. The models and datasets that you build will be used to improve the efficiency of the go-to-market process and empower our product, sales and marketing teams to provide timely and relevant content, support and experiences to our users. Your work will also enable the Growth team to rapidly experiment and iterate on its strategies, helping to drive critical decisions on how we shape the Fivetran product and services.
This is a full-time position based out of our Toronto office.
Technologies You'll Use
SQL, dbt, Python, BigQuery, Looker, Sigma, Census, GitHub, NewRelic
What You'll Do
- Create, maintain and optimize business-critical workflows
- End to end ownership of data models, pipelines, cost, monitoring and quality
- Create operational analytics environment to support new models and tools
- Design, deploy and maintain tools, systems and datasets that enable product, sales, marketing teams, analysts and data scientists to deeply understand the Fivetran customer journey and operationalize relevant targeting, segmentation and engagement
- Unify data from multiple sources owned by multiple departments
- Apply business-oriented approaches to working with data
- Develop a detailed understanding of how users engage with Fivetran product and services
Skills We're Looking For
- 3+ years experience in data engineering or similar field
- Advanced SQL in a modern data warehouse environment
- Effective use of scripting languages such as Python
- Ability to balance performance, cost and quality
- Experience with dbt
- Ability to self-govern and apply best practices
- Strong communication skills and a desire to thrive in a highly cross-functional environment
- Curiosity and a love for solving ambiguous, evolving problems
Nice-to-haves
- Experience working in BigQuery
- Experience setting up an analytics environment from the ground up
- Experience working in B2B software, data products or other technical software products
- Experience collaborating directly with product, engineering, marketing and data scientists
- Experience with customer and marketing data
- Experience with experimentation use cases