Senior Data Engineer

Fimador; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Fimador is seeking a Principal Data Engineer to lead strategic, hands-on data platform initiatives in a tech-bio setting. You will design, build and operate scalable pipelines that power analytics, AI/ML and enterprise applications, while ensuring governance, quality and security.

The role focuses on enabling Generative AI and RAG use cases with well-curated data and robust indexing for semantic search. You will influence architectural decisions, balance immediate delivery with maintainability,

Qualifications

• Significant hands-on experience building and operating production data pipelines for analytics, AI/ML and enterprise apps.
• Experience enabling Generative AI and Retrieval-Augmented Generation (RAG) use cases via data pipelines.
• Knowledge of data quality, lineage, governance and access controls and their impact on performance.
• Familiarity with cloud data platforms and tooling, including Databricks and AWS in production environments.

Responsibilities

• Design, build and operate scalable data pipelines in production environments.
• Influence data engineering decisions balancing near-term delivery with long-term maintainability.
• Ensure data platforms support analytics, AI/ML and enterprise workflows.
• Support GenAI, NLP and discovery via well-curated datasets and pipelines.

Skills

Data pipelines

GenAI

RAG

Data governance

Cloud Databricks AWS

NLP / AI discovery

Tools

Databricks

AWS

Job description

Fimador is currently looking to identify a Principal Data Engineer to join a tech-bio firm in a critical role as they evolve their data platforms.

Operating at principal level, the role is strategic yet hands-on, focusing on building, operating and continuously improving reliable, scalable and compliant data capabilities that support AI, analytics and enterprise workflow applications.

You’ll have the opportunity to influence data engineering decisions through deep practical expertise, balancing near-term delivery with long-term maintainability and ensuring data platforms can sustainably support growing product, data and regulatory demands.

They are looking for someone with significant hands-on experience building and operating production data pipelines that support analytics, AI/ML and enterprise application use cases.

A key area will be enabling Generative AI and Retrieval-Augmented Generation (RAG) use cases through high-quality, well-governed data. This could include building pipelines that prepare and curate structured and unstructured datasets for retrieval, supporting document ingestion, chunking and enrichment workflows, and ensuring data is appropriately indexed and accessible for semantic search and LLM-powered applications.

Experience supporting vector search, embeddings, metadata management and retrieval pipelines would be highly beneficial, alongside an understanding of how data quality, lineage, governance and access controls impact the performance and reliability of RAG-based systems.

Familiarity with cloud-based data platforms and tooling, including Databricks and AWS, in production enterprise environments is desirable, as is experience supporting GenAI, NLP, AI-driven discovery or reporting through well-designed data pipelines and curated datasets.