> Markdown version of [/jobs/ext/2008328-data-engineer](https://www.wearedevelopers.com/jobs/ext/2008328-data-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** BESPOKE LAB INCORPORATED - **Location:** Rochester, MN, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Cloud Computing, Information Engineering, Extract Transform Load (ETL), JSON, Python (Programming Language), NumPy, Management of Software Versions, Parquet, Pandas, Machine Learning Operations, Docker - **Published:** August 9, 2026 - **Apply:** https://www.adzuna.com/details/5829651922 ## About the Role 3+ years of data engineering experience - pipelines, ETL, data modeling in production or research settings Strong Python proficiency (numpy, pandas, Parquet, HDF5 are daily tools) Familiarity with at least one RL framework (Gymnasium / OpenAI Gym, dm_env, or equivalent) and working knowledge of RL environment structure - observation/action spaces, reward signals, episode logic Experience with data versioning and experiment tracking (DVC, MLflow, W&B, or similar) Comfortable with Docker and cloud infrastructure (AWS or GCP) Solid grasp of ML storage formats: Parquet, HDF5, JSON Lines ## Description You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments - and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Tips and Tricks for Working with JSON](https://www.wearedevelopers.com/videos/1229-tips-and-tricks-for-working-with-json) - [Vectorize all the things! Using linear algebra and NumPy to make your Python code lightning fast.](https://www.wearedevelopers.com/videos/562-vectorize-all-the-things-using-linear-algebra-and-numpy-to-make-your-python-code-lightning-fast) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Python Data Visualization @ Deepnote (w/ PyViz overview)](https://www.wearedevelopers.com/videos/113-python-data-visualization-deepnote-w-pyviz-overview) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production)