Future Tech Jobs
Future Tech Jobs
Engineers who design, build, and maintain the foundational data infrastructure that powers modern data-driven organisations. A critical role in ensuring data is accessible, reliable, and scalable.
Data Platform Engineers are the architects and custodians of an organisation's data infrastructure. They design, build, and maintain the systems that enable data to flow seamlessly from source to destination, ensuring that data is accessible, reliable, and scalable. This role is distinct from data science and machine learning engineering, focusing instead on the underlying data pipelines, data warehouses, and data lakes that support data-driven decision-making. Data Platform Engineers work closely with data scientists, analysts, and other stakeholders to ensure that the data infrastructure meets the organisation's needs.
A typical week for a Data Platform Engineer is a mix of designing and implementing new data pipelines, maintaining and optimising existing infrastructure, and collaborating with cross-functional teams.
Based on advertised midpoints across the 27 priced listings posted in the last 12 months. Base salary only.
% of 12 listings posted in the last 12 months that mention each skill, extracted from job descriptions.
A typical UK progression for data platform engineers. Years are guidance — strong people move faster, and many senior folks sidestep into research, product or management.
Assists in the design and implementation of data pipelines, with a focus on learning and supporting more senior engineers.
Takes ownership of specific data pipelines and infrastructure components, ensuring they are reliable and scalable.
Leads the design and implementation of complex data infrastructure projects, mentoring junior engineers and driving best practices.
Strategises and oversees the entire data infrastructure, influencing organisational data architecture and leading cross-functional initiatives.
There's no single route, but most people follow some version of these steps.
Start by gaining a solid understanding of data engineering fundamentals, including ETL processes, data warehousing, and SQL.
Gain hands-on experience with data pipeline tools and technologies, such as Apache Kafka, Apache Spark, and cloud data services.
Focus on designing and implementing robust data platforms, including data lakes and data warehouses, to support data-driven applications.
Take on leadership roles, managing complex data infrastructure projects and mentoring junior engineers.
Strategise and influence the overall data architecture of the organisation, driving innovation and best practices.
The role involves designing, managing, and maintaining a secure and scalable cloud-based data platform for the Connells Group. You'll work within a technical team using Agile methodologies, implementing Platform as Code and cloud observability while supporting incident resolution and capacity management. The position requires strong technical skills in Microsoft Fabric, SQL Server, and cloud technologies, with an emphasis on continuous improvement and collaboration.
The role involves developing, maintaining, and optimising a cloud-based data platform on Microsoft technologies, with a focus on reliability, performance, and scalability. The engineer will support data solutions across Azure and Microsoft Fabric, implement DataOps practices, troubleshoot platform issues, and collaborate with technical teams to enable scalable data capabilities and analytical workloads via Power BI.
The role involves designing, managing, and maintaining a secure and scalable cloud-based data platform using Microsoft Fabric and SQL Server. You'll work within a technical team to resolve incidents, implement platform-as-code practices using tools like Terraform and GitHub, and ensure operational resilience through proactive monitoring and capacity management. The position supports enterprise data strategy while operating across legacy and modern systems in an Agile environment.
Design and operate a secure, scalable Azure data platform using Databricks, Data Lake, and Data Factory. Build data ingestion and transformation pipelines while implementing governance, security, and automation best practices. Collaborate with architects to deliver data products and support the platform roadmap.
Design, build, and maintain scalable data platform solutions including data pipelines, data lakes, and analytics architectures using Python, PySpark, and SQL. Collaborate with technical teams and business stakeholders within an Agile environment to deliver high-quality, secure data systems. Work with modern cloud platforms such as Microsoft Fabric, Databricks, or Snowflake to support enterprise reporting and decision-making.
Design and maintain data pipelines, lakehouses, and data warehouses within Microsoft Fabric using PySpark, Python, T-SQL, and DAX. Employ Infrastructure as Code, Git, and Azure DevOps for scalable, secure data platforms while ensuring data quality and compliance. Collaborate with stakeholders to enhance analytics and business intelligence through innovative engineering solutions.
Lead and manage a global engineering team to design and implement enterprise-wide data lineage and quality capabilities on Barclays' cloud data platform. Drive technical strategy across a hybrid cloud ecosystem using AWS, Snowflake, Databricks, and open-source tools like OpenLineage. Enable trusted, traceable data flows for regulatory, finance, and business reporting across a product-led operating model.
Senior AWS Data Platform Engineer (Fixed Term Contract)When registering to this job board you will be redirected to the online application form. Please ensure that this is completed in full in order that your application can be reviewed.We’re looking for...
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Data Platform Engineers commonly use tools like Apache Kafka, Apache Spark, AWS Redshift, Google BigQuery, and various cloud data services to build and manage data infrastructure.
A Data Platform Engineer focuses on building and maintaining the data infrastructure, ensuring data is accessible and reliable. A Data Scientist, on the other hand, uses this data to perform analysis and build models.
Key skills include strong programming abilities, knowledge of data storage and retrieval systems, experience with ETL processes, and the ability to design scalable and secure data pipelines.
The typical career progression includes moving from Junior to Senior, then to Principal Data Platform Engineer, with increasing responsibilities and leadership roles.
Salaries for Data Platform Engineers can vary widely based on experience, location, and industry. For more detailed salary information, please refer to the salary section on this page.
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