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Technical Project Manager delivering network infrastructure projects — enterprise networking, Wi-Fi and CCTV deployments — while leading engineering teams and managing customer stakeholders. Uses PRINCE2/PMP-style project management and works with networking vendors such as Palo Alto and Juniper.
An Analytics Engineer in London who designs and maintains scalable ETL/ELT pipelines and curated datasets on cloud platforms (AWS preferred), optimising SQL data models and backend structures to power reliable reporting, self-service analytics, and performant BI dashboards.
Contract Analytics Engineer supporting an ecommerce business: builds and maintains data pipelines, creates dashboards and reports, and collaborates with the data engineering team on a GCP stack using BigQuery and Looker/LookML. London hybrid, outside IR35, daily rate 525-575.
Data engineer at a data-driven SaaS company in Bristol (hybrid) who designs, builds, and maintains scalable data pipelines and keeps the data platform reliable and secure. Core stack includes Spark, Airflow, and Kubernetes, with mentorship from senior engineers and a path toward senior-level responsibilities.
A Senior Data Engineer in Bristol who designs and delivers scalable cloud data pipelines (Python, PySpark, SQL, Airflow/ADF-style orchestration) for an asset-management SaaS analytics platform, integrating sources into a single source of truth for fund and portfolio performance while mentoring teammates.
A hands-on data engineer role at an expanding ecommerce business: you build and maintain data pipelines on the company's newly adopted GCP stack and create dashboards and reports in BigQuery and Looker/LookML to enable analytics and data-driven decisions across the organization.
Contract Data Engineer designing and maintaining data ingestion pipelines in a modern Azure/Databricks environment. Day to day involves building ETL/ELT processes using Medallion Architecture, incremental and batch loads, and transformations with Python, dbt, Azure Data Factory, and Databricks Lakeflow.
Senior Data Engineer designing, building and optimizing a cloud data platform for a fast-growing hospitality brand, working hybrid from London. Day to day: developing scalable pipelines on Azure Databricks, driving data quality and governance, and partnering with data scientists, analysts and business stakeholders to turn raw data into trusted insights.
A London-based data engineer who designs, builds and optimises scalable ETL/ELT pipelines and curated data models on cloud platforms (AWS preferred) to power reporting and self-service analytics. Works closely with BI developers and stakeholders, with a focus on SQL, data quality, governance and platform improvement.
Overview In this role you will develop backend and platform capabilities for two core insurance products, joining a small, agile, and collaborative team. You will focus on delivering robust backend solutions while…
Overview In this hands-on, full-stack Software Engineer role you will help build a market-leading cloud platform for a growing SaaS business. You’ll work with an experienced team to deliver new features and tackle…
Tria Recruitment is seeking a Senior Data Engineer in London to design and grow a world-class data platform. You’ll work on Databricks, Azure, and data lakehouse architectures, delivering scalable pipelines and…
Senior Data Engineer who designs, builds, and optimizes a cloud data platform on Azure Databricks for a global hospitality brand, developing scalable pipelines and driving data quality, governance, and analytics. Permanent hybrid role in London (3 days on-site) supporting decisions across supply chain, marketing, sales, and store operations.
Backend-focused data engineer on a BI team: designs and maintains ETL/ELT pipelines, builds business-ready datasets, and optimises data models and SQL query performance, working with AWS cloud data platforms, Python/PySpark, and BI tools like Power BI and Tableau.
Hybrid Full-Stack Engineer role requiring 3 days in Bristol office, delivering frontend/backend features using Python (Django/FastAPI), JavaScript, Docker/Kubernetes, and applying AI-driven capabilities where appropriate.
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