Senior Forward Deployed Engineer

DCV Technologies; Greater London; Hybrid; GBP 90,000 - 150,000; Full time

Job summary

DCV Technologies in London is seeking a Senior Forward Deployed Engineer who blends hands-on software and data engineering with direct client delivery. You will embed with client teams, translate evolving stakeholder needs into features, and drive delivery across time zones.

The role requires strong Python (Pandas, Pyomo, Scikit-Learn), data pipelines, dashboarding (Plotly Dash/Bokeh), and cloud/deployment expertise (AWS, Docker, CI/CD). English essential; Spanish is a plus.

Qualifications

• Hands-on Python development with Pandas and scientific libraries.
• Experience building data pipelines for time-series data.
• Ability to translate client needs into actionable features.

Responsibilities

• Embed with client teams to understand business problems.
• Lead delivery through senior engineers and manage relationships.
• Design and implement dashboards for decision support.
• Own data architectures and validation pipelines.
• Collaborate across Europe and North American time zones.

Skills

Python

Pandas

Data engineering

Dashboards

AWS

Docker

CI/CD

PostgreSQL

NoSQL

Client liaison

Advanced degree

Time zone collaboration

Education

Advanced degree in quantitative field

Tools

Plotly Dash

Bokeh

Pyomo

Scikit-Learn

RabbitMQ

PostgreSQL

Job description

Position: Senior Forward Deployed Engineer
Location: London, UK (2-3 days /week onsite)
Permanent position

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