The Enterprise Data & Intelligence (EDI) team at Asana is tasked with building powerful decision-making data products, integrations, process automation tools, and analytical reports. We are looking for a driven Data Engineer to add to our growing team who will be fundamental to the company’s operations by supporting the data science, business and finance teams. You will accelerate the business by connecting systems and data seamlessly
This role is based in our Warsaw 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 your recruiter can share more about the in-office requirements We offer a Contract of Employment (UoP) for our employees in Poland
What you’ll achieve Build and deliver scalable data pipelines using modern cloud-based architectures, optimizing data reliability and performance
Develop new API integrations to streamline and enhance data accessibility across business functions
Collaborate with Data Science and Business teams to develop analytical solutions, unlocking actionable insights through data analysis, investigation, and visualization
Influence best practices in Databricks and cloud-based data engineering, driving innovation and adoption across teams
Establish trust and strong relationships across technical and business teams, ensuring alignment on data strategy and execution
Lead process automation efforts and proactively identify optimisation opportunities, improving data workflows and ensuring scalability
Implement monitoring, alerts, and compliance controls to ensure data accuracy, availability, and security
Be the go-to expert for data solutions and integrations, providing guidance and technical mentorship to team members
Create accurate and clear technical documentation to standardize processes and enhance knowledge-sharing
About you Degree in Computer Science, Engineering or equivalent technical field experience 4+ years of hands-on experience in Data Engineering or Software Engineering
Fluent in SQL and proficient in at least one programming language (e.g., Python, Java, Scala etc.) Strong expertise in Databricks, AWS S3, Spark and Airflow Knowledg