Senior Data Engineer
Asana
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Compensation
Salary & market context
105% above the BLS national median
BLS national median: $74,680
- To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.
- In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits.
- We strive to provide equitable and competitive benefits packages that support our employees worldwide and include: Mental health, wellness & fitness benefits Career coaching & support Inclusive family building benefits Long-term savings or retirement plans In-office culinary options to cater to your dietary preferences #LI-Hybrid About us Asana is a leading platform for human + AI collaboration.
Requirements
Top 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 about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making At Asana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission.
- If you're interested in this role and don't meet every listed requirement, we still encourage you to apply.
- The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process.
Perks & setup
Benefits candidates care about
- To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.
- In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits.
- We strive to provide equitable and competitive benefits packages that support our employees worldwide and include: Mental health, wellness & fitness benefits Career coaching & support Inclusive family building benefits Long-term savings or retirement plans In-office culinary options to cater to your dietary preferences #LI-Hybrid About us Asana is a leading platform for human + AI collaboration.
Why candidates care
Benefits & perks
- To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.
- In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits.
- We strive to provide equitable and competitive benefits packages that support our employees worldwide and include: Mental health, wellness & fitness benefits Career coaching & support Inclusive family building benefits Long-term savings or retirement plans In-office culinary options to cater to your dietary preferences #LI-Hybrid About us Asana is a leading platform for human + AI collaboration.
Start here
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 about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making At Asana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission.
- If you're interested in this role and don't meet every listed requirement, we still encourage you to apply.
- The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process.
Responsibilities
What you'll do
- 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.
- 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 about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making At Asana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission.
Role snapshot
About 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
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