Data Developer in London

Requirements

• We have previous experience as a Data Developer, Data Engineer, or Data Analyst, ideally in a fast-paced environment.
• We work autonomously with exceptional attention to detail and accuracy.
• We have high proficiency in SQL and either Python, R, or Java.
• We have experience with data manipulation packages, ETL pipeline tools, data visualization platforms, and data modelling software.
• We have technical expertise in data models, data pipeline design, and structuring unstructured or free-text data into usable formats.
• We have experience working with cloud data warehouses such as Snowflake, including building data lakes, managing free-text and unstructured storage, and modelling data into structured tables.
• We have experience building and publishing data products and interactive dashboards using data visualization tools.
• We have experience applying AI and large language models to extract, contextualise, and structure data from unstructured sources, with an understanding of prompt engineering and AI-assisted data workflows.
• We have experience designing or working with ontologies and entity-relationship models, with hands-on graph database experience such as Neo4j, Memgraph, or Cypher.
• We have hands-on experience with graph analytics, modelling and querying knowledge graphs, traversing entity relationships, and surfacing patterns from connected data.
• We have experience designing and deploying search platforms such as Elasticsearch or Open Search, including index schema design, hybrid retrieval pipelines, and integration with LLM-powered natural language query layers.
• We manage stakeholder expectations, lead partnerships, and deliver projects, initiatives, and commercial targets cross-functionally.
• We have exceptional verbal and written communication and collaboration skills.
• We demonstrate our values of being Collaborative, Innovative, Responsible, Agile, Brave, and Enthusiastic.
• Desirable: we have proficiency in mathematical computing.
• Desirable: we are familiar with CRM or ESP environments such as Hub Spot or Mail Chimp.
• Desirable: we are familiar with RAG architectures, including data chunking, embedding, and vector indexing workflows.
• Desirable: we have experience with AI orchestration frameworks such as Lang Chain, Llama Index, or Haystack.
• Desirable: we have knowledge of vector databases for AI-powered search and retrieval such as Pinecone, Weaviate, or pgvector.
• Desirable: we understand AI governance principles, including bias detection, explainability, and responsible AI data handling.
• Desirable: we can coach and train others to understand and use our tools and environments.

Responsibilities

• We design, build, maintain, and optimise our database infrastructure and data pipelines in a warehouse environment while continuously improving data quality.
• We develop and maintain data ingestion processes, including web crawling and scraping using frameworks such as Scrapy or Firecrawl, and extract data from diverse sources using AI tools.
• We build and maintain data transformation processes within the warehouse environment for use in data visualisation and self-service platforms.
• We design and populate structured data models and tables that capture entities through their lifecycle, and we build ontologies to map relationships between entities, including graph database structures where appropriate.
• We design and manage AI-powered search and indexing pipelines, including index schema design, vector index construction, semantic search configuration, and natural language query layer design.
• We build and publish data products, including interactive dashboards, that turn structured data into actionable intelligence for subscribers, clients, and internal teams.
• We support and lead projects for the development of business insight and strategy through our analytics tools and data modelling software.
• We create and discover new tools and processes to keep our team at the forefront of analytics technology.
• We lead projects autonomously to produce new data-oriented commercial products and enhancements to existing ones, including cross-functional projects.
• We manage ownership of specific data development and data engineering functions.
• We formulate and assess hypotheses and manage stakeholders expectations around development and delivery.
• We host discussions around decision-making.
• We develop and maintain strong stakeholder relationships to scope and deliver new commercial opportunities end-to-end.
• We manage cross-functional deliverables to improve collaboration and enable business growth.
• We train and upskill potential new analysts.

Technologies

• AI
• Open Search
• Cloud
• CRM
• ETL
• Elastic Search
• Graph Database
• Hub Spot
• Support
• Java
• LLM
• Neo4J
• Network
• Python
• SQL
• Snowflake
• Web
• Machine Learning
• Marketing

More

We are Aspermont, a global leader in business‑to‑business media, data, and intelligence services with a 190‑year publishing legacy and trusted brands across mining, energy, and agriculture.

We operate a global network of over 100 journalists and analysts, serving a professional audience in more than 190 countries from our headquarters in London, with offices in Australia, Brazil, the Philippines, and Singapore.

Our business has transformed into a scalable digital platform underpinned by proprietary technology and data infrastructure.

You will join our Data Analytics Department, where we support the business globally and deliver high‑grade data and analytics for subscribers, clients, and internal teams.

We offer flexible working with a hybrid setup between home and our London office, plus full‑time hours of 37.5 per week and We Work perks including:

• free barista coffee
• weekly events and classes
• pool and foosball tables
• inspiring workspaces
• #J-18808-Ljbffr