Senior Algorithm Engineer

New
G
GorillaEnergy SaaS
If you apply from Germany, this is a remote roleContractSenior
Salary not disclosed
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Job Details

Required Skills
PythonSQLNumpyPandasMicroservicesPySpark

Requirements

  • Proven experience designing, developing, and deploying algorithms or data models (for example forecasting, pricing, or optimisation) in production environments.
  • Strong proficiency in Python.
  • Experience with the modern data engineering stack such as SQL, Pandas, NumPy, SciPy, Dask, Polars, DuckDB, or PySpark.
  • Experience designing, building, maintaining, and evolving microservice architectures and distributed systems.
  • Experience working with large-scale or high-frequency datasets such as smart meter, weather, or IoT data.
  • Familiarity with SaaS or software product environments.
  • Technical leadership capabilities, including influencing design decisions, promoting best practices, and driving alignment across teams.
  • Proven experience mentoring and supporting the development of other engineers through code reviews, documentation, and collaborative problem-solving.
  • Ability to clearly explain technical concepts to both technical and non-technical audiences.

Responsibilities

  • Design and implement algorithms for forecasting, pricing, and optimisation that can scale across markets and data volumes.
  • Lead technical design discussions and guide architectural decisions for high-volume data processing and modelling.
  • Translate complex business and energy-market requirements into performant, maintainable, and explainable data solutions.
  • Improve the robustness, performance, and scalability of existing models and workflows.
  • Mentor peers through code reviews, technical guidance, and knowledge sharing.
  • Collaborate closely with Product, Data, and Delivery teams to ensure accuracy, usability, and reliability in production.
  • Contribute to Gorilla’s growing library of reusable components and frameworks that raise the standard for data and algorithmic excellence.
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