Future Tech Jobs
Future Tech Jobs
The backbone of modern data infrastructure. Building, maintaining, and optimising the pipelines that power data-driven decisions.
Data Engineers are the architects and builders of the data infrastructure that underpins modern businesses. They design, build, and maintain the data pipelines, warehouses, and lakes that enable organisations to store, process, and analyse vast amounts of data. Whether working in scaleups, research-heavy startups, or the larger consultancies, Data Engineers play a crucial role in ensuring that data is accessible, reliable, and secure.
A typical week for a Data Engineer is a mix of coding, testing, and collaboration with cross-functional teams.
Based on advertised midpoints across the 137 priced listings posted in the last 12 months. Base salary only.
A typical UK progression for data engineers. Years are guidance — strong people move faster, and many senior folks sidestep into research, product or management.
Assists in building and maintaining data pipelines, with a focus on learning and supporting more senior team members.
Takes ownership of specific data pipelines and projects, ensuring they meet performance and reliability standards.
Leads the design and implementation of complex data infrastructure, mentoring junior engineers and collaborating with cross-functional teams.
Strategises and oversees the entire data infrastructure, driving innovation and best practices across the organisation.
There's no single route, but most people follow some version of these steps.
Start with foundational skills in SQL, Python, and data storage systems. Gain experience with ETL processes and data warehousing.
Work on building and maintaining data pipelines using tools like Apache Kafka and Apache Spark. Focus on efficiency and scalability.
Optimise data storage and retrieval processes to ensure high performance and reliability. Collaborate with data scientists and analysts.
Take ownership of complex data infrastructure projects. Mentor junior engineers and ensure best practices are followed.
Strategise the overall data infrastructure, driving innovation and best practices. Oversee the implementation of new technologies and methodologies.
This role involves leading the design, build, and optimization of a modern Azure Databricks Lakehouse platform. You will work closely with engineers and stakeholders to ensure the platform is scalable, secure, and reliable, while taking ownership of key data platform initiatives and driving technical excellence.
This role involves building and optimizing end-to-end data pipelines using Databricks, PySpark, and Spark SQL. You will act as a subject matter expert, partnering with stakeholders to gather requirements and drive continuous improvement in a newly established data function within a global organization.
This role involves designing and building robust data pipelines using Azure services, optimizing data workflows in Databricks, and managing data ingestion processes, including real-time streaming with Kafka. The Data Engineer will work closely with data analysts, architects, and business stakeholders to ensure high-quality data solutions and maintain data governance and performance best practices.
This role involves designing, building, and maintaining scalable data pipelines and data products using modern ELT principles. You will work closely with product managers, architects, and engineers to deliver data solutions aligned with business needs, ensuring high-quality, well-documented code and maintaining strong engineering standards. The team is focused on developing a scalable Data Mesh architecture in a collaborative, product-led environment.
This role involves supporting the development and maintenance of cloud-based data pipelines, assisting in the design and optimization of data models, and working with analytics teams to ensure high-quality data outputs. You'll be part of a collaborative and forward-thinking data team, gaining exposure to cutting-edge technologies and best practices in data governance.
This role involves designing, developing, and maintaining scalable data pipelines for Celonis, supporting major transformation programmes in finance, operations, and supply chain. You will work hands-on with SQL Server, Microsoft Fabric, and Python, translating business requirements into technical data solutions and ensuring data quality and governance.
This senior Data Engineer role involves designing, building, and maintaining data pipelines in GCP and BigQuery, transitioning from legacy SQL systems to cloud-native architectures. You will lead projects, work closely with stakeholders, and focus on improving reliability and automation in a small, focused team.
This role involves taking ownership of a cloud-based data platform on GCP, building and maintaining robust ingestion pipelines, and designing high-quality data models to support analytics and self-serve BI. You will work closely with analytics and commercial teams to translate business needs into technical solutions, ensuring data reliability and scalability while contributing to data governance and platform improvements.
This role involves designing and maintaining end-to-end ELT and ETL pipelines within a large-scale AWS environment, building well-structured data models, and improving data quality and governance. You will lead architectural decisions, support transformation projects, and mentor a junior engineer in a digital-focused financial services organization.
This role involves leading the design, development, and delivery of cloud-based data platforms within a Data Mesh environment. You will work closely with product managers, architects, and engineers to solve complex technical challenges, build robust ETL/ELT pipelines, and mentor junior colleagues.
This role involves designing and maintaining large-scale data pipelines, optimizing AWS Redshift for performance and cost, and building ML-friendly datasets. You'll work on greenfield projects and integrate new data sources, directly impacting the company's machine learning and customer ROI.
This role involves designing, building, and optimizing cloud-based data pipelines and warehouses for a fast-growing financial services company. You will shape data architecture, improve processes, and mentor a junior engineer while working in a collaborative, agile environment with a focus on innovation and governance.
This role involves designing, building, and maintaining modern data platforms and analytics solutions for public sector clients. You will work with technologies like Databricks, Spark, Azure, and AWS, focusing on data warehousing, lakehouse platforms, and CI/CD practices in a hybrid working environment.
As a Data Engineer, you will be responsible for maintaining and optimizing the organization's data platform, including SQL Server databases and a modern cloud-based data ecosystem. You will ensure data reliability, scalability, and performance, develop robust data pipelines, and collaborate with cross-functional teams to deliver end-to-end data solutions. The role involves hands-on technical work, continuous improvement, and a focus on data governance and quality.
This role involves building and maintaining scalable data pipelines using Python, Spark, and Azure technologies. You'll work closely with stakeholders to automate manual processes, support data modelling, and drive best practices in a growing data function. The position offers a mix of Data Engineering and Data Science responsibilities, providing hands-on technical work with significant business impact.
The locations with the most live listings for this role today.
Data Engineers commonly use tools like Apache Kafka, Apache Spark, SQL, Python, and data warehousing solutions such as Amazon Redshift or Google BigQuery.
Collaboration with data scientists is crucial. Data Engineers need to understand the data needs of data scientists to build effective data pipelines and infrastructure.
Key skills include proficiency in SQL, Python, and data storage systems, as well as a strong understanding of ETL processes, data warehousing, and big data technologies.
The typical career progression is from Junior Data Engineer to Data Engineer, then Senior Data Engineer, and finally Principal Data Engineer, with increasing levels of responsibility and leadership.
For specific salary information, please refer to the salary section on this page, which is updated with the latest data from live job listings.
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