Data Engineer

Das ist der Job

You will accelerate the business by connecting systems and data seamlessly.

Darum lohnt es sich

Overview 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. Responsibilities Build and deliver scalable data pipelines using modern cloud‑based architectures, optimizing data reliability and performance.

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. Be the go‑to expert for data solutions and integrations, providing guidance and technical mentorship to team members.

Benefits Generous, transparent and fair compensation system (base salary and generous Restricted Stock Unit for Asana Inc.)&am #J-18808-Ljbffr 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. Develop new API integrations to streamline and enhance data accessibility across business functions.

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. Create accurate and clear technical documentation to standardise processes and enhance knowledge‑sharing.

Qualifications 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.

Knowledge of system and software engineering architecture principles, concepts, and best practices. Proactive self‑starter with a proven ability to identify opportunities, propose innovative solutions, and execute them effectively. Ability to handle high‑impact stakeholders with professionalism and composure, even under pressure.

Strong analytical and problem‑solving skills with a proactive approach to issue resolution. Excellent communication skills, with the ability to clearly articulate complex technical concepts to non‑technical stakeholders. Demonstrable experience with data visualisation would be an advantage.

Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision‑making.