Optimizing Scalable Time Series Data Storage Solutions Expert

vor 17 Stunden

Berlin, Berlin, Deutschland Terra One Climate Solutions GmbH Vollzeit
About Terra One Climate Solutions GmbH

We are a fast-growing company focused on building the future of renewable energy at Terra One Climate Solutions GmbH. Our mission is to advance sustainable energy solutions and lead the path to climate neutrality.

As a data-driven company, we process massive amounts of energy-related data to power machine learning models and optimize energy trading decisions. We handle vast amounts of dynamic, versioned time series data critical for ML models and trading decisions.

This includes diverse forecasts relevant in the energy market (like weather, solar and wind) generated at high frequencies. Our datasets encompass a wide range of energy-related information crucial for the renewable energy sector.

Master Thesis Topic: Efficient Methods for Storing and Accessing Versioned 2D Time Series Forecast Data

The goal of this thesis project is to explore and implement efficient storage and retrieval solutions for high-frequency, versioned time series data.

Benchmarking these solutions for scalability, speed, and integration into our existing architecture is also a key aspect of this project.

  • Designing an optimized solution that balances performance with maintainability will be a crucial task in this thesis.
Your Responsibilities:
  • Research and evaluate approaches for versioned time series data storage, including time-series databases, columnar storage, and other innovative methods.
  • Set up and test different database systems and configurations (e.g., InfluxDB, TimescaleDB, PostgreSQL, MongoDB, BigQuery).
  • Benchmark these solutions against key metrics: query speed, scalability, storage efficiency, and compatibility with Python workflows and GCP/Digital Ocean infrastructure.
  • Explore and improve our key use case: retrieving historical snapshots of forecast data efficiently
  • Ensure that the proposed solutions handle diverse forecast data types, including solar, wind, weather, demand, hydro, cooling, thermal generation, and cross-border flow capacities.
  • Collaborate with the data engineering team to ensure the proposed solution integrates seamlessly into our current tools and workflows.
Compensation Package

The estimated salary for this position is €48,000 per year, depending on qualifications and experience.

This compensation package also includes access to our cutting-edge data environment, diverse forecasting challenges, supportive team, resources, flexibility, and contract covering the duration of your thesis writing.

Who Fits Well with Us?
  • You are pursuing a Master's degree in a relevant field (e.g., Computer Science, Information Systems, Environmental Informatics, Renewable Energy, or related).
  • You have strong programming skills in Python (or other language) and experience with data manipulation libraries.
  • You are familiar with databases and storage systems (e.g., MongoDB, SQL/NoSQL databases, cloud storage).
  • Knowledge of cloud infrastructure (e.g., GCP, Digital Ocean) and workflow orchestration tools (e.g., Airflow) is a plus.
  • You thrive in a structured, self-driven environment and are eager to tackle a real-world problem with significant business impact.

Please note that location is Berlin, Germany but remote work is possible.

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