
Maritime Data Engineer
10 hours ago
At Maritime Optima, we are seeking a talented Data Engineer to join our tech team. In this role, you will apply your data wrangling, data engineering, machine learning, and software development skills to build and maintain our core data pipelines and modeling efforts.
About Us
We are a company that specializes in maritime intelligence, providing innovative solutions for the industry. Our team is passionate about using technology to solve complex problems, and we are looking for someone who shares our vision.
Key Responsibilities
- Systemize vessel data acquisition from structured and unstructured sources.
- Transform data using Pandas and/or PySpark, ensuring data quality and consistency before integration into our Databricks environment.
- Work closely with QGIS and custom PyQGIS scripts to maintain and improve our custom geospatial dataset for ports, berths, anchorages, etc.
- Generate specialized data sets, such as banned areas, by classifying H3 cells and merging spatial data from multiple sources.
- Collaborate with the team to refine manual processes and automate geospatial dataset generation where possible.
- Troubleshoot and debug data issues, performing manual curation when necessary.
- Contribute to data storage and retrieval solutions that support real-time and batch processing.
- Contribute to PySpark data pipelines on Databricks, ensuring they run reliably and efficiently.
- Contribute to Machine Learning (ML) models for vessel parameter prediction, vessel destination prediction, and cargo flow analysis.
- Evaluate model performance, track metrics, and iterate rapidly to improve accuracy and reliability.
Technical Expertise
- Proven track record with data wrangling tasks, leveraging columnar transformations in Pandas or similar data manipulation packages.
- Familiarity with Spark or similar big data processing frameworks.
- Prior experience with QGIS or other GIS tools is advantageous.
- Hands-on experience with big data processing on Databricks is a plus.
- Solid understanding of classical ML (boosted regression tree models, regression, clustering) and familiarity with implementation details of deep learning networks.
- Comfortable iterating on models based on feature engineering and model evaluation metrics.
- Strong analytical thinking and problem-solving abilities.
- Willingness to handle both automated and manual dataset generation tasks.
- Great collaborative skills necessary for working in a cross-disciplinary team with backend, frontend, data scientists, and commercial people.
- Excellent communication skills.
- Professional working proficiency in English, preferably also Norwegian.
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