Climate17 is working with a leading specialist energy transition advisory firm to appoint a Technical Analyst / Senior Technical Analyst into a high‑impact, high‑ownership role.
Our client is an established and highly respected consultancy operating at the forefront of European energy markets, advising major utilities, infrastructure funds, and investors on complex commercial and strategic questions across power and gas markets.
This position sits at the intersection of engineering, data, modelling and AI. It offers the opportunity to build the technical backbone that underpins investment‑grade analysis and client‑facing insight.
The Opportunity
This is a role for someone with a strong engineering foundation and a builder’s mindset. You will work close to the commercial and consulting teams, translating real‑world market questions into robust technical systems.
The centre of gravity is Python engineering, data platform development, and modelling infrastructure. There is also a strong opportunity to shape how AI tools are embedded into consulting workflows. You will have meaningful autonomy and influence over technical architecture, standards, and tooling.
Key Responsibilities
Build and Operate a Modern Data Platform
- Design and maintain data pipelines to ingest, validate, and publish curated datasets used in modelling and dashboards.
- Establish robust data quality, observability, monitoring, and documentation practices.
- Develop scalable database and storage architectures, including lake/lakehouse concepts (partitioning, schema evolution, versioning, governance).
- Apply strong SQL and data modelling principles to support performance and reliability.
Strengthen the Energy Modelling Environment
- Develop reusable Python packages and services supporting market scenario modelling and investment workflows.
- Improve reproducibility and reliability of modelling runs (configuration management, structured logging, versioned scenarios).
- Raise engineering standards across testing, code review, CI/CD, and maintainable architecture.
Implement Scalable AI Solutions (Agents + RAG)
- Prototype and productionise internal AI tools to support research, drafting, document extraction, synthesis, and knowledge search.
- Build end‑to‑end RAG systems including ingestion pipelines, embeddings, retrieval strategies, reranking, evaluation frameworks, and monitoring.
- Ensure safe‑by‑design implementation, with appropriate access controls, auditability, and data governance.
Desirable: Develop Lightweight UI Tools
- Create simple web applications and dashboards enabling analysts and clients to explore data and model outputs.
- Translate business requirements into intuitive user experiences backed by secure APIs.
Example Project Ownership
- Building a curated time‑series lakehouse covering fundamentals, prices, and market curves with lineage and quality controls.
- Developing a scenario management system enabling versioned, reproducible market simulations.
- Deploying a permission‑controlled RAG assistant across internal research, models, and deliverables.
- Supporting development of a client‑facing data portal.
- Designing interactive dashboards to explore sensitivities and scenario comparisons.
Candidate Profile
- Quantitative degree (Engineering, Mathematics, Physics, Computer Science, Statistics or similar).
- 3+ years’ experience building production‑grade software or data systems.
- Strong Python engineering capability beyond notebook environments.
- Strong SQL and data modelling expertise.
- Ability to take ownership of ambiguous problems and deliver structured, production‑ready solutions.
- Clear communication and documentation skills.
- Rapid learner, comfortable working across evolving technologies.
Advantageous
- Experience with data platforms and database architecture.
- UI development experience (React + JavaScript/TypeScript or similar).
- AI engineering exposure.
- Experience building RAG systems and working with vector databases.
- Docker, CI/CD, deployment practices and secrets management.
- Energy markets exposure (not essential; sector knowledge can be developed).
Why This Role?
- Work on tools that directly inform high‑stakes investment decisions.
- Operate in a technically ambitious but commercially grounded environment.
- High autonomy and scope to shape architecture and engineering standards.
- Meaningful exposure to European energy transition dynamics.
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