> Markdown version of [/jobs/ext/3838250-data-platform-lead-energy-trading](https://www.wearedevelopers.com/jobs/ext/3838250-data-platform-lead-energy-trading). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Platform Lead - Energy Trading

- **Company:** Strike IT Services
- **Location:** London, UK
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Information Engineering, Data Infrastructure, Software Design Patterns, Python (Programming Language), Power BI, OpenLink Endur, Standard Sql, Azure Data Lake, Data Streaming, Azure Data Factory, Data Pipelines, Powerapps, Databricks
- **Published:** October 20, 2026
- **Apply:** https://www.careerboard.com/gb/en/find-jobs-in-United-Kingdom/-72E93ADB2642814889/

## About the Role

* Strong hands-on experience with Databricks, Azure Data Factory (ADF) and Azure Data Lake Storage (ADLS).
 * Strong SQL and Python development skills.
 * Proven experience in data modelling, data engineering design patterns, and batch and streaming data processing.
 * Understanding of energy or commodity trading, key trading entities and the data supporting trading processes.
 * Experience translating business needs into scalable data products and clear technical requirements.
 * Strong understanding of data quality, governance, lineage and traceability.
 * Ability to work effectively across business stakeholders, engineers and architects, combining technical depth with delivery ownership.

Desirable Experience

 * Exposure to Openlink Endur and its trading data.
 * Knowledge of LNG trading processes.
 * Experience with Power BI and Power Apps.
 * Previous ownership of a trading data platform or data product roadmap.

## Description

* Own the platform vision, strategy and roadmap, aligning priorities with trading, LNG and reporting requirements.
 * Translate business requirements and complex trading processes into clear data product requirements, priorities and acceptance criteria.
 * Drive the end-to-end data life cycle, from source systems such as Endur, through ingestion, standardisation, enrichment and historical storage in Databricks, to curated datasets, reports and extracts.
 * Work closely with engineering and architecture teams to define data models, design patterns and implementation approaches, balancing scalability, performance, maintainability and reuse.
 * Establish data quality, governance and lineage, including validation rules, exception handling and traceability of critical data attributes.
 * Support the design and delivery of batch and streaming pipelines using Azure Data Factory, Azure Data Lake Storage and Databricks.
 * Act as the link between business and technology teams, ensuring platform capabilities meet practical trading and operational needs.