Job Description

Built on meritocracy, our unique company culture rewards self-starters and those who are committed to doing what is best for our customers.

Data Analytics Engineer

Location: Hybrid - London

Package: Negotiable + Benefits

The day to day:

As a Analytics & AI Data Engineer within the Data Team, you will sit at the intersection of data engineering and analytics—designing robust, scalable data foundations while generating insights that support operational and strategic decision‑making. The role provides end‑to‑end ownership of data workflows, including ingestion, transformation, modelling, analysis, and testing. You will also play a key role in advancing our AI‑enabled data capabilities, including unstructured data handling, vector search, LLM‑ready architectures, and AI‑assisted engineering practices.

Core Purpose

To build and maintain scalable data pipelines and platforms, and to analyse and interpret data to generate insights, reports, and recommendations that deliver business value.

The day to day:

• Data Engineering:

  • Design, build, and maintain ETL/ELT pipelines for ingesting, transforming, and storing data from multiple sources.

  • Ensure data quality, integrity, and reliability through automated testing and validation.

  • Manage and optimise databases, data warehouses, and cloud data environments (e.g. Azure/AWS).

  • Collaborate with Data Operations to ensure platform stability and operational excellence.

• Analytics & Insight

  • Collect, clean, and analyse structured and unstructured data to identify trends and actionable insights.

  • Develop dashboards and reports using BI tools such as Power BI or Tableau.

  • Communicate findings clearly to both technical and non‑technical audiences.

  • Prepare datasets for AI/ML use cases, including feature engineering, dataset shaping, and data labelling.

• AI & Advanced Data Capabilities

  • Design and enhance pipelines supporting unstructured data, vector embeddings, and semantic search.

  • Contribute to data architectures that enable LLM integrations, AI agents, and cloud‑native AI workloads.

  • Apply AI‑assisted engineering practices, such as code generation, documentation automation, and quality checks.

  • Use AI‑enabled analytical tooling to accelerate pattern discovery, validation, and problem investigation.

• Collaboration & Delivery:

  • Work closely with Data Operations and Data Services Leads to balance priorities and resource allocation.

  • Partner with Technical Leads to ensure solutions align with established technical guardrails and best practices.

  • Engage with business stakeholders to understand requirements and translate them into deliverable solutions.

  • Collaborate with Data Scientists and AI Engineers on model deployment, vector database integration, and monitoring.

• Continuous Improvement:

  • Champion a culture of learning, innovation, and process optimisation.

  • Proactively introduce new tools, automation opportunities, and analytical approaches.

  • Explore emerging frameworks and implement practical improvements.

• Governance & Compliance:

  • Ensure all data activities comply with governance, privacy, and security standards.

  • Contribute to data management initiatives, documentation, and best practices.

About you:

• Degree in a STEM subject or equivalent experience.

• Strong programming skills (Python, SQL, R, or similar).

• Experience with cloud data platforms (Azure, AWS, GCP) and big data technologies (Spark, Hadoop).

• Knowledge or experience with Denodo is an advantage.

• Proficiency in BI and data visualisation tools (Power BI, Tableau).

• Solid understanding of data modelling, ETL/ELT processes, and database management.

• Analytical mindset with strong problem‑solving and communication skills.

• Ability to work collaboratively across multidisciplinary teams and engage with stakeholders at all levels.

• Commitment to continuous learning and professional development.

• Awareness of modern AI/LLM concepts and the ability to support AI‑ready data engineering, including vector embeddings, semantic search, and use of AI service APIs (Azure OpenAI, Gemini, etc.).

• Experience shaping data for advanced analytics or ML, including feature extraction and dataset quality checks.

• Understanding of cloud‑based AI workloads and MLOps deployment and monitoring patterns.

The rewards:

• A negotiable basic salary and all the normal benefits you’d expect (Holiday, company pension etc.)

• A collaborative, open and honest environment that is designed to deliver the best outcomes to our clients and staff

• A flexible working methodology to enable you to be where you need to be, if you don’t need to be in an office then don’t, if you want to be in an office your welcome to use one.

• An environment built around supporting and developing our staff with funding available for relevant professional qualifications.

We are an Equal Opportunity Employer. We take pride in the diversity of our team and seek diversity in our applicants.