Data Engineer
The data team designs, implements and scales data pipelines that transform raw data into actionable models and metrics that enable insight. This team owns the pipelines that transport and process database data from all of Asana’s product surfaces. We build and operate the infrastructure and services that ensure data accuracy and data availability for data scientists, analysts, and business and product teams.
We are looking for a data engineer to found our product data engineering team. This team will have ownership of the core data pipelines powering Asana’s metrics and partner with our existing data infrastructure team, data science team, and cross-functional partners to help evolve our analytic data model as data volume grows and new needs arise to support the growth of the business.
What you’ll achieve
- Architect, build, and launch scalable data pipelines to support Asana’s growing data processing and analytics needs. Some upcoming projects you may work on include designing and implementing pipelines that deliver data with high quality, consistency, and timeliness. Evangelize high-quality software engineering practices for building data infrastructure and pipelines at scale.
- Produce foundational data tables and metrics with clear definitions, lineage, and test coverage to ensure that data is reliable, intelligible, and maintainable
- Understand and influence logging frameworks and practices to support our data flow, architecting logging best practices where needed
- Implement systems to track data quality and consistency
- Partner with business domain experts, data scientists and analysts, and engineering teams to build a roadmap for foundational data sets that are aligned with business goals and that enable self-service. Some upcoming projects you may work on include evolving data models and schemas based on business, product, and engineering needs to facilitate data-driven decisions and features across Asana. Drive the collection of new data and the refinement of existing data sources; develop relationships with product engineering teams to manage our analytic data model as the Asana product evolves.
About you
- Bachelor’s degree in Computer Science, Math, Statistics, Engineering, or a related quantitative field, or equivalent experience
- 5+ years of industry experience in software engineering or data engineering
- Experience using coding languages Python, Java, Scala
- Experience using workflow management engines (e.g. Airflow, Luigi, Prefect, Dagster, digdag.io, Google Cloud Composer, AWS Step Functions, Azure Data Factory, UC4, Control-M)
- Experience with Hadoop or similar ecosystem (MapReduce, Yarn, HDFS, Hive, Spark, Presto, Pig, HBase, Parquet)
- Effective in working across team boundaries to establish overarching data architecture, and provide guidance to individual teams
- Expertise in relational databases and query authoring (SQL)
About us
At Asana, we're building a better way to work, fueled by transparency, inclusion, and technology that is a force for positive change. Asana is a work management platform that helps teams orchestrate their work, from daily tasks to strategic initiatives, so they can move faster and accomplish more with less. For the past 5 years, we've been named a top workplace, including top 10 Great Place to Work Best Small & Medium Workplaces, #1 Fortune Best Workplace in the Bay Area for four years in a row, #8 Fortune Best Workplaces for Women, #14 Glassdoor Best Place to Work, and one of Ireland's Best Workplaces. With offices all over the world, we are always looking for curious, collaborative, and mission-driven people to help us enable the world’s teams to work together effortlessly.
We believe in supporting people to do their best work and thrive, and building a diverse, equitable, and inclusive company is core to our mission. Our goal is to ensure that Asana upholds an inclusive environment where all people feel that they are equally respected and valued, whether they are applying for an open position or working at the company. We welcome applicants of any educational background, gender identity and expression, sexual orientation, religion, ethnicity, age, citizenship, socioeconomic status, disability, and veteran status.