Primary record

Senior Data Engineer

Asana Indexed employerVancouver, BC · Vancouver, British Columbia, Canada
Source-hosted applyChecked 4h agoOther
Apply at Asana

Asana receives this application through Greenhouse. Babu Careers does not claim delivery.

Workplace

hybrid

Employment

Other

Published

Aug 11, 2026

Closes

No date supplied

The role

The Data Engineering team’s mission is to ensure high-quality data to enable data-informed decision-making across Asana. You will build data artifacts that are leveraged by Product and Business Data Science teams to optimize our user adoption, growth, and experience. In this role, you will partner with the Infrastructure team to build a self-service analytics platform for the company. This role is based in our Vancouver office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday; most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.

What you’ll achieve

• Design, implement, and scale end-to-end data products that support growing data processing and analytical needs

• Transform raw data into actionable insights to drive product strategy and power in-depth analyses and reporting

• Leverage AI to build self-serve tools and accelerate Data/GTM workflows

• Partner with data scientists, domain experts, and engineering teams to develop a roadmap that aligns with our business goals

• Implement systems that guarantee data quality, governance, and availability

About you

• 5+ years of experience in Data Engineering or Software Engineering

• Experience in data modeling and building scalable data pipelines involving complex transformations

• Proficiency in data processing and storage technologies like Databricks, AWS/S3, Python/Scala/Java, SQL, Spark, and Airflow

• Proactive and innovative in identifying and addressing performance bottlenecks in existing workflows

• Motivated to work closely with cross-functional partners to evolve our analytical data model

• Demonstrates curiosity a

Requirements

Department: Data Engineering