You’ll be joining a team of passionate developers to work on projects for local and international companies as well as in academic research. This will involve different phases of the end-to-end delivery – direct contact with the client, business analysis of the problem, coming up with an appropriate solution, implementation and moving it to the production environment. You’ll be directly cooperating with machine learning team members, either by leading the project or assisting in various stages.
MS/PhD (or BS +3-4 years industry experience) in Computer Science or related fields
3 years minimum working with data-intensive projects
Independent worker - as the company's only Data Engineer, it's imperative that this candidate can independently drive forward data priorities
Expertise with relational databases and SQL querying and scripting
Expertise in Python
Demonstrated ability to write high-quality, production-ready code (readable, well-tested, with well-designed APIs)
Familiarity with DevOps related concepts / tools (e.g. Docker, Kubernetes, Terraform)
Passion for architecting large distributed systems with elegant interfaces that can scale easily.
Experience in areas relevant to data engineering, including data management, custom ETL design and data modeling.
Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions
Familiarity with cloud computing services (AWS or GCP)
Familiarity with web services and application frameworks (Django, Flask, FastAPI)
Proficiency in Linux environment (including shell scripting), and experience with version control practices and tools
Experience with working with machine learning and/or data scientist stakeholders in accelerating workflows
Experience with large-sized data sets and associated technologies such as Spark/Big Query/Hive/Flink/Kafka, etc.
Nice to Have
Expertise additional general-purpose programming languages (such as Java, Scala, C/C++, or Go)
Hands-on experience with Cloud Data Warehouse (Snowflake or Redshift) and Big Data technologies (e.g S3, Hadoop, Hive, Spark, Flink, Kafka, etc).
Working knowledge of statistics and various flavors of statistical modeling techniques
Experience with deploying ML models
Experience with MLOps related concepts / tools (e.g. MLFlow/Neptune/Kubeflow/W&B)
Salary: 11 000 - 17 000 PLN + VAT (B2B)