Your challenge 🚀
- Build a truly self-service application for business users so they can work with data even without learning SQL or needing assistance from more technically-skilled colleagues. We are democratizing access to data and making it available for anyone within an organization who needs it.
- Find ways to automate most activities users must do to reduce the time needed to prepare data, allowing them to actually use the data for their work, and make data-driven decisions.
- Create a product that contains all the features enterprise solutions must-have, while making it super-easy to use. We want to refute the myth that enterprise software must be ugly and painful to use–it’s a lie!
- Take end-to-end ownership of the whole product and not just blindly focus on coding.
What you’ll do 💻
- Co-design, extend, improve, operate and optimize the Python microservices and workers utilizing both established and in-house machine learning algorithms (relationship discovery, recommendation, anomaly detection, deduplication, and more to come).
- Participate in discussions about new features and closely cooperate with our researchers, so you’ll be contributing and learning at the same time.
- Leverage a cloud-native environment and distributed computing to power and continuously compute insights derived from connected data at scale.
Is this you? 💪
- You might not tick all the boxes but we still want to hear from you!
- Hands-on experience with applied machine learning or data science products.
- You enjoy constantly learning new things and sharing your knowledge with others.
- You have prior experience using SQL databases, distributed systems and/or ETL/ELT workflows (Dask, Prefect, Airflow).
- You know how to deploy code to a Kubernetes cluster (Argo, Kustomize/Helm)
- You’re not afraid to propose new approaches supported by sound reasons, yet willing to find a win-win solution that may sometimes be different from your original idea.
- You can clearly communicate your progress, ask for help, provide non-threatening feedback, and document your results.
- You’re used to/willing to adopt the DevOps mindset (how well the app is operated in production is your business) and learn more about deploying applications to a Kubernetes cluster.
- You prefer prevention and proactivity over firefighting and hacking.
- You are physically located in UTC-1 to UTC+3 time zones.
Our technical stack 👨💻
- Frontend: TypeScript, React/Vue, Apollo, Nx, MobX, Styled Components
- Backend: Java, Spring Boot, Kotlin, GraphQL, Python, jOOQ
- Big data: Spark, Redshift, Snowflake
- Storage: Postgres, Elastic, Minio
- Infrastructure: GitLab CI/CD, Kubernetes, AWS, Azure
Your team 😍
- You will be part of Data Stories Spaceport.
- If you want to learn more about our Product & Engineering structure, how it works, and why our teams are called Spaceports, you can take a look at our Chief Product & Technology Officer Martin Zahumensky’s articles where he describes this and more in full detail.
What happens next? 🔜
- We’ll quickly review your application and let you know whether we’re a good fit to move forward. This won’t take longer than a day.
- You’ll have your first chat with Šárka or Michal, just so we can get to know each other better, understand your motivation for applying, and make sure you know all the important things about us.
- Depending on your seniority, you may have another interview or two with teammates from the AI/ML Circle and Lukáš, your hiring manager.
- We’ll finish the interviews with lunch, so you can meet your future team.
- The whole process shouldn’t take longer than a week or two.
We offer equal opportunities
Ataccama is proud to be an Equal Opportunity Employer. We know diversity fuels knowledge exchange, fosters innovation, and empowers us to grow and be better as a company and as humans. We seek to recruit, develop, and retain the most talented people from a diverse candidate pool.
We are committed to fair and accessible employment practices. If you are contacted for a job opportunity, please let us know how we can best meet your needs and advise us of any accommodations required to ensure fair and equitable access throughout the recruitment and selection process.