Master Thesis Student – Optimizing Scalable Time Series Data Storage (m/f/d)

About Us:

Welcome to Terra One – an exciting, fast-growing company focused on building the future of renewable energy. 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. Join us as we push the boundaries of what’s possible in renewable energy technology.

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

At Terra One, we handle vast amounts of 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. Managing this dynamic, versioned time series data efficiently while ensuring compatibility with our current infrastructure is the key.

This thesis will focus on:

• Exploring and implementing 3–5 different storage and retrieval solutions for high-frequency, versioned time series data.
• Benchmarking these solutions for scalability, speed, and integration into our existing architecture.
• Designing an optimized solution that balances performance with maintainability.

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.

What We Offer:

• Cutting-Edge Data Environment: Work with 11 data sources, 500 datasets, over 1TB of raw data, and >1 billion data points driving our ML and trading decisions.
• Diverse Forecasting Challenges: Gain experience working with complex datasets including weather, energy demand, hydro, and cross-border capacities.
• Supportive Team: Mentorship from a team of experienced data engineers and ML practitioners.
• Resources: Access to our infrastructure, including GCP, Digital Ocean, MongoDB, and Python-based workflows.
• Flexibility: The freedom to explore innovative solutions with guidance and feedback from experts.
• Contract: A fixed-term 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.

Location: Berlin, Germany (but remote would be possible)

Diversity & Inclusion Statement:

At Terra One, we value diversity and firmly believe that different perspectives enhance our innovative strength. We welcome applications from all candidates, regardless of gender, ethnic origin, religion, belief, age, sexual identity, or disability. We are committed to an open corporate culture characterized by respect and mutual appreciation. Our goal is to create a work environment that is accessible and inclusive for everyone. We look forward to meeting you and working together to create a sustainable future.