Data/Machine Learning Engineer (m/f)
Pontis Technology d.o.o.
- Zagreb
- Stalni radni odnos
- Puno radno vrijeme
- Act as the primary technical point of contact for the project, supporting day-to-day delivery and participating in technical discussions with stakeholders
- Design, build, and maintain core platform components, including data pipelines, ingestion, and validation workflows
- Continuously improve data workflows to enable faster, more reliable iteration and delivery
- Collaborate closely on technical direction while independently driving execution and delivery
- Translate loosely defined business requirements into clear technical tasks, solutions, and outputs
- Support rapid iteration cycles by incorporating real-world feedback into ongoing development
- Contribute to overall platform quality, performance, and robustness through hands-on development and optimization
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field
- 3+ years of hands-on experience in data engineering and/or machine learning in a production environment
- Hands-on experience with big data platforms such as Microsoft Fabric or Databricks, including work on data science projects
- Experience building and shipping data-driven products or features used by real users
- Strong experience designing, building, and maintaining scalable end-to-end data pipelines (including ETL processes, ingestion, transformation, validation, and deployment)
- Solid understanding of core data engineering concepts, including data modeling, medallion and lakehouse architectures, as well as data quality and monitoring practices
- Experience with cloud environments (preferably Microsoft Azure; AWS or GCP also acceptable)
- Strong knowledge of SQL, with experience working with data warehouses, NoSQL databases, and data lake storage solutions
- Experience working with semi-structured data (e.g. JSON, logs, external APIs) and transforming it into usable datasets
- Ability to independently own problems from definition to delivery, including stakeholder alignment and iteration
- Experience working with domain-specific data in pharmaceutical, supply chain, or regulatory environments
- Experience combining and reconciling multiple external data sources with differing schemas and quality levels
- Experience integrating and working across multiple external datasets, including familiarity with concepts such as ontology design and entity resolution
- Familiarity with ERP or planning systems (e.g. SAP, Kinaxis, OMP) and integrating their data