Data Engineer

Habitat Energy is a fast-growing technology company focused on the physical and financial optimization of energy storage and renewable generation assets globally through complex models and trading. By maximizing the returns from these assets, we aim to drive investment in renewable energy and accelerate the transition to a low-carbon world. Our team of 130+ people in Austin, TX, Oxford, UK, and Melbourne, Australia brings together talented experts in energy trading, data science, software engineering, and renewable energy management. We have a vacancy for a Data Engineer to join our Austin-based team. Responsibilities Supporting Data Engineering Infrastructure: Contribute to the design, development, implementation, and continuous improvement of our data engineering tools, workflows, processes, and platforms. This includes enhancing architectural foundations and integrating new data management technologies. Writing Well-Structured Code: Develop clean, maintainable, well-documented code that adheres to best practices. Support best coding practices within Habitat's software, machine-learning, and data science teams. Enhance Data Engineering Knowledge: Improve expertise within the software team and ensure their ability to support and collaborate on the data infrastructure. Data Quality Management: Continuously enhance data quality across multiple dimensions such as accuracy, availability, performance, and accessibility to ensure a clear understanding of data within the company. Operational Support: Providing backup/escalation to the tech-on-call team. Communication: Communicating effectively across Software and Data Science teams. Requirements Preferred Skills and Experience 3+ years of Python experience. 3+ years of working in technical teams, building data pipelines, delivering productionized code, building/maintaining live applications, developing tooling, and improving backtesting frameworks. Experience in applying relational database design. Proficiency with Orchestration and IaC in AWS (e.g., Terraform, Kubernetes, RabbitMQ, Airflow, Prefect), Git, containerization (Docker), and database management (e.g., Postgres, Alembic). Fluent in Python and its wider numerical ecosystem (e.g., Pandas, NumPy, Polars, Pydantic). Nice to Have Skills and Experience 2+ years of orchestrating machine learning workflows. Experience with OSS data warehousing tooling and management. Cloud infrastructure experience. Experience with monitoring frameworks (e.g., Prometheus). Experience archiving data to Parquet on S3 and creating tools for API/Grafana queries. Experience centralizing diverse datasets for analytics, visualization, and machine learning. Familiarity with time-series forecasting and/or optimization. Experience with data visualization and dashboards (e.g., Grafana, Superset). Familiarity with machine learning and associated techniques (feature engineering, boosting methods, LightGBM). Benefits In return, we offer a competitive salary, flexible working arrangements, and significant personal development opportunities. We operate a hybrid working model with at least 2 days in our office in Austin. We value diversity and our environment is supportive, challenging, and focused on the consistent delivery of high-quality, meaningful work. #J-18808-Ljbffr Habitat Energy