> Markdown version of [/jobs/ext/2688095-data-engineer-with-modelling-experience-de](https://www.wearedevelopers.com/jobs/ext/2688095-data-engineer-with-modelling-experience-de). 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 Engineer with Modelling Experience (DE) - **Company:** Infinity Quest - **Location:** UK - **Salary:** £52,024.0 - **Contract:** Permanent contract - **Skills:** Geographic Information Systems, Airflow, BigQuery, Cloud Computing, Cluster Analysis, Databases, Continuous Integration, Directed Acyclic Graph (Directed Graphs), Information Engineering, Data Governance, Data Manipulation Languages, Data Warehousing, Network Topologies, Identity and Access Management, Python (Programming Language), Metadata, Query Optimization, Simple Data Format, SQL Databases, Google Cloud, Sql Optimization, Gitlab, Containerization, Graphql, Terraform, Data Pipelines - **Published:** September 3, 2026 - **Apply:** https://www.adzuna.co.uk/jobs/details/5867507491 ## About the Role We are seeking a skilled Data Engineer with strong modelling experience across data warehouse and graph paradigms. The ideal candidate is proficient across the GCP data stack, CI/CD pipelines, infrastructure-as-code, and data governance tooling, and can operate independently in a complex cloud-native environment., SQL & BigQuery * Advanced SQL (window functions, arrays and structs, DDL, DML, UDFs, CTEs) * Dataform for SQL modelling and transformation tasks * BigQuery computational model - partitioning, clustering, query optimisation, pricing model (on-demand vs slots) * Knowledge Catalog integrations: CDE identification, metadata, policy tagging, data quality scans (Data Contracts) * Understanding of BigQuery IAM access principles * Experience using GraphQL Python * Proficient Python development for data engineering tasks Data Modelling * Data warehouse and graph modelling * Normalisation and denormalisation * Conceptual, logical, and physical modelling * SCD and time series modelling * Medallion architecture concept * Translation of business requirements into modelling outputs Airflow / Composer * DAG creation and execution * Utilising Airflow in a cloud environment * Integration with GCS, BigQuery, and Dataform GCS (Google Cloud Storage) * Bucket and blob structure * Storage classes and retention policies * Bucket access management via IAM GitLab * Branch management, commits, merges, repository maintenance * CI/CD pipeline setup and execution in GitLab Terraform (IaC) * Terraform fundamentals and GitLab integration * Deploying and modifying repeatable modules SpannerDB * Querying Spanner databases * Relational modelling and schema design (primary keys, interleaved/global indexes) * Use of interleaved tables, strong vs stale reads Pub/Sub * Understanding of event-driven messaging with Pub/Sub GIS Data * Knowledge of GIS data and engines (coordinate conversions, common file formats, BigQuery GIS) Domain Knowledge * Telecommunications: network topology, KPIs, telemetry, asset lifecycle Stakeholder Management * Proven experience in stakeholder engagement on large-scale projects ## Description * Design, build, and maintain scalable data pipelines and transformation workflows * Implement and manage CI/CD pipelines within GitLab * Deploy and maintain Terraform modules for repeatable infrastructure provisioning * Develop and orchestrate Airflow DAGs in Google Cloud Composer * Model data at warehouse and graph levels to support platform requirements * Manage SpannerDB schema design and querying * Apply BigQuery knowledge catalog and data governance practices * Collaborate with stakeholders and contribute to large-scale project delivery ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [WeAreDevelopers LIVE - Modern DevOps for IoT Devices and More](https://www.wearedevelopers.com/videos/1805-wearedevelopers-live-modern-devops-for-iot-devices-and-more) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Enabling automated 1-click customer deployments with built-in quality and security](https://www.wearedevelopers.com/videos/83-enabling-automated-1-click-customer-deployments-with-built-in-quality-and-security) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)