Data Engineer

Taylor Hopkinson Limited
London, City And County Of the City Of London, United Kingdom
4 months ago
Applications closed

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Job Type
Permanent
Work Pattern
Full-time
Work Location
On-site
Seniority
Mid
Education
Masters
Posted
24 Apr 2026 (4 months ago)

Data Engineer for a major offshore wind project in The United Kingdom

Responsibilities

Design and implement scalable ingestion pipelines from multiple source systems including and internal business data sources.

* Ensure reliable, automated, and monitored data flows into the Bronze layer of the Medallion architecture.

* Work within clients existing security framework to establish compliant connectivity to operational data sources.

* Build and maintain Silver and Gold layer transformations in Databricks using Python and SQL.

* Onboard datasets into Unity Catalog, ensuring proper governance, lineage, and discoverability. Platform Collaboration & Delivery

* Support the ML/Data Scientist in preparing clean, structured datasets for anomaly detection and asset performance modelling.

* Contribute to technical documentation and ensure pipelines are maintainable and transferable.

* Stay current on Databricks and Azure platform developments relevant to the stack.

* Support the Digital & AI Strategy Manager in assessing feasibility of new data source integrations as the roadmap evolves.

Experience

* Master's degree in Computer Science, Data Engineering, Software Engineering, or a related technical field.

* Professional certifications in Azure, Databricks preferred

* Training or background in energy systems, renewable energy, offshore wind or BESS technologies is a strong plus.

* 4-7 years of hands-on data engineering experience in a cloud environment.

* Demonstrated experience delivering production pipelines on Databricks and Azure (ADLS Gen2, ADF or equivalent).

* Proven ability to implement Medallion architecture or equivalent layered data modelling patterns.

* Experience with REST API ingestion and integration of business systems (ERP, finance tools).

* Experience in a contractor or project-based delivery model preferred.

* Exposure to OT/SCADA environments or energy sector data.

* Exposure to MLOps workflows or collaboration with data science teams

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If you have been watching AI job boards over the past year, one title keeps surfacing again and again: the forward deployed engineer, or FDE. It has gone from a niche term known mainly to Palantir alumni to arguably the hottest role in the entire AI hiring market. Job postings for forward deployed engineers have exploded, salaries have climbed past levels most software engineers will ever see, and the biggest names in AI — OpenAI, Anthropic, Google, Salesforce, Databricks and Palantir — are all competing for the same small pool of talent. So what exactly is an AI forward deployed engineer, why has demand surged so dramatically, and how do you position yourself to land one of these roles? This guide breaks it all down for AI engineers, software engineers and data scientists looking at their next move.