Our client specialises in using advanced algorithms and AI to manage and maximise the value of energy storage. By optimising the timing of battery charging and discharging based on real-time market conditions, customers can participate more effectively in multiple energy markets, enhancing the efficiency and profitability of renewable energy resources. We are now looking for a ML Ops / Data Engineer to join their busy, growing and highly successful team.
ML Ops / Data Engineer
Oxford - Hybrid working from home up to 4 days per week.
£75-80K plus excellent benefits package.
To be successful in this role:
We are looking for someone who is a great fit for the company. We want people who take accountability, build trust and are innovative. Specific requirements for this role include:
* 5+ years of Python experience
* 3+ years of working in technical teams, building data pipelines, delivering productionised code, building/maintaining live applications, developing tooling and improving backtesting frameworks
* 2+ years of orchestrating machine learning workflows
* Proficiency with Orchestration and IaC in AWS (e.g. Terraform, Kubernetes, RabbitMQ, Airflow), Git, containerisation (Docker), database management (e.g. Postgres, Alembic)
* Fluent in Python and its wider numerical ecosystem (e.g. Pandas, NumPy, Polars, Pydantic)
Additional desirable but not essential requirements for this role include:
* Relational database design
* 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 centralising diverse datasets for analytics, visualisation and machine learning
* Familiarity with time-series forecasting and/or optimisation
* Experience with data visualisation and dashboards (e.g. Grafana, Superset)
* Familiarity with machine learning and associated techniques (feature engineering, boosting methods, LightGBM)
Position summary:
Our client is looking for smart, motivated people who share a belief that they can outperform the energy sector dinosaurs, have a positive impact on the planet and have fun doing it together.
Job role and responsibilities:
As a ML Ops / Data Engineer, you will be responsible for:
* 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 the architectural foundations and integrating new data management technologies
* Writing Well-Structured Code: Develop clean, maintainable, well-documented code that adheres to best practices. Mentor and support in the continued improvement of coding practices within the Data Science team
* Enhance data engineering knowledge: Improve expertise within the software team and ensure their ability to support and collaborate on the data science 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
* Providing backup/escalation to the tech-on-call team
* Communicating effectively across Software and Data Science teams
Benefits:
The business values diversity and their environment is highly supportive, challenging and focused on the consistent delivery of high quality, meaningful work. You will receive a competitive salary, flexible working arrangements and a lot of personal development opportunities.
We encourage you to apply even if you may not meet every requirement in this posting.