This role involves designing and building analytics-ready data models, enabling self-service reporting, and delivering trusted datasets to support strategic business decisions. You will work closely with stakeholders to translate business requirements into robust data solutions, using SQL and cloud data platforms like GCP/BigQuery.
This role involves designing and maintaining scalable data pipelines, integrating data from various business systems, and developing robust data models. You will work closely with stakeholders to translate requirements into usable data assets and support the growth of the data function.
This role involves leading the design and development of analytics-ready data models and transformation pipelines within a Databricks Lakehouse environment. Responsibilities include maintaining KPI definitions, ensuring data quality, and working closely with Data Architects, BI Developers, and business stakeholders to translate requirements into effective data solutions.
The Energy Analytics Engineer will design and maintain data pipelines using Azure-based tools, automate data ingestion from APIs, and support reporting and analytics for energy and sustainability initiatives. The role involves close collaboration with cross-functional teams to deliver robust data models, ensure data quality, and enable data-driven decision-making. A key focus is on enabling carbon reporting and driving digital solutions that support Veolia’s ecological transformation goals.
The Data Analytics Engineer will develop and deliver high-quality analysis, reporting, and insights across the organisation. Responsibilities include creating dashboards, automating processes, and supporting new data-led initiatives, with a focus on financial inclusion and public benefit.
This role involves leading the migration and optimization of log ingestion pipelines from Splunk to Cribl, designing resilient pipelines, and working closely with SOC and IR teams to ensure security logs are reliably ingested and tuned for detection. You will also monitor and document pipeline health and operational procedures.
This role involves designing and maintaining data transformations, building scalable data products, and enabling reliable analytics through close collaboration with analysts and business stakeholders. The engineer will work extensively with SQL, cloud data platforms, and dbt to create trusted datasets that power business intelligence and decision-making. Emphasis is placed on best practices in analytics engineering, data modelling, and automation within a mature data environment.
This role involves building and optimizing Power BI semantic models, refining and promoting reports from domain workspaces into central production, and establishing a company-wide KPI glossary. You will also focus on DAX optimization, deployment pipelines, and row-level security.
This role involves leading data architecture and building solutions using Azure SQL, Azure Databricks, .NET/C#, and Power BI. You will work across the entire project lifecycle, from requirements gathering to training end users.
This role involves setting the technical strategy and architecture for a data platform, leading a team of Data Engineers, and ensuring the platform's reliability, scalability, and cost efficiency. You will work on a Microsoft Fabric platform and have a strong focus on data modelling and pipeline engineering.
This role involves leading the modernization of core data platforms using Microsoft Azure technologies, including Azure Synapse, Azure SQL Server, and Microsoft Fabric. You will work on enhancing data pipelines, ensuring data reliability and scalability, and collaborating with BI and analytics teams to support advanced analytics and executive decision-making.
This role involves designing, developing, and optimizing scalable data pipelines and cloud-based data warehousing solutions. You will work closely with Data Engineers, Analytics Engineers, and other technical teams to improve the performance, reliability, and scalability of the data platform, ensuring data is effectively used across the business.
The Data Engineer will design and build a modern, cloud-first data platform from the ground up, migrating from legacy on-premise systems to a scalable cloud architecture using tools like BigQuery and Airbyte. The role involves refactoring complex T-SQL into cloud workflows, implementing CI/CD and version control with Git, and creating robust data pipelines to support analytics and future AI/ML initiatives. This is a high-ownership role shaping the foundation of Liquidline’s data strategy.
This role involves building and maintaining a Python codebase and data pipelines, developing REST APIs, and creating internal tools for data ingestion, validation, and reporting. You will work closely with a senior engineer to solve real business problems and contribute to the growth of the company's internal data platform.
This role involves designing and implementing robust data ingestion pipelines, developing scalable storage solutions, and ensuring data quality and usability. You will collaborate with data scientists and software engineers, apply data parsing and transformation techniques, and mentor team members.
