Senior Forward Deployed Engineer (Energy)

Infoplus Technologies UK; Greater London; On-site; GBP 100,000 - 150,000; Full time

Job summary

Infoplus Technologies UK is seeking a senior computational scientist / forward deployed engineer who can blend data engineering, backend development and client delivery. You will sit with client teams, translate needs into features, and drive delivery end-to-end.

You will work across data pipelines, optimization, dashboards and production deployment on AWS, Docker, and CI/CD, collaborating with stakeholders across Europe and North America time zones and guiding junior engineers.

Qualifications

• Strong Python for data and backend work with Pandas, Pyomo, and Scikit-Learn.
• Experience building data pipelines, time-series data, and KPIs.
• Ability to lead client-facing delivery and guide junior engineers.

Responsibilities

• Owns client relationships and leads regular delivery sessions.
• Translates evolving stakeholder needs into features and roadmaps.
• Guides junior engineers and sets coding and testing standards.
• Defines workstreams from loosely scoped problems to deliverables.

Skills

Python (data/backend)

Pandas

Pyomo/Scikit-Learn

Data pipelines

Dashboarding

AWS

Docker

CI/CD

Client relationship management

Team leadership

Education

Advanced degree in quantitative field

Tools

AWS

Docker

Plotly Dash

Plotly

PostgreSQL

Oracle

NoSQL Cassandra

RabbitMQ

Pyomo

Scikit-Learn

Pandas

Job description

Job Description

• We've had strong results with a profile that blends hands‑on software/data engineering with direct client delivery - someone who embeds with a client team, understands their commercial problem, and builds and ships the tooling to solve it. We want more of this, at a senior / lead level: someone who can own the client relationship, scope ambiguous problems independently, and guide more junior engineers, not just execute a defined spec.
• A computational scientist / forward deployed engineer who can move fluidly between data pipelines, backend logic, optimization/simulation, and client‑facing dashboards - and deploy it all to production. The defining trait is the combination of genuine engineering depth with the maturity to sit in front of clients, translate evolving stakeholder needs into features, and drive delivery.
• Strong Python for data and backend work - Pandas plus optimization/scientific libraries (e.g. Pyomo, Scikit-Learn)
• Building simulation, forecasting, and KPI/analytics frameworks to model financial or operational outcomes
• Data engineering: ingestion and transformation pipelines for time-series / market data, schema design, automated validation/testing (e.g. pytest)
• Interactive dashboarding (e.g. Plotly Dash, Bokeh, or similar) for decision support
• Cloud and deployment: AWS, Docker, CI/CD across dev/QA/prod; message queues (e.g. RabbitMQ) a plus
• Databases: PostgreSQL, plus exposure to NoSQL (e.g. Cassandra) and Oracle
• Owns client relationships and runs the cadence (regular working sessions, requirements gathering, alignment)
• Scopes loosely defined problems into deliverable workstreams with minimal direction
• Can technically lead on a delivery team
• Sets engineering standards (testing, deployment hygiene, code quality)
• Working with non-technical stakeholders, problem framing mindset.
• Advanced degree in a quantitative field (statistics, analytics, computer science, engineering or similar)
• Able to collaborate across European and North American time zones
• English essential; Spanish a strong plus