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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Head of Data Engineering - **Company:** Careerwise - **Location:** London, UK - **Experience:** Expert - **Salary:** £149,500.0 - **Contract:** Temporary contract - **Skills:** Artificial Intelligence, Data Analysis, Microsoft Azure, Continuous Integration, Data as a Services, Data Architecture, Data Control, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Security, Data Systems, DevOps, Python (Programming Language), Machine Learning, Meta-Data Management, Cloud Services, Standard Sql, DataOps, Azure Data Factory, Microsoft Fabric, Infrastructure Automation Frameworks, Data Management, Azure Synapse Analytics, Data Pipelines, Databricks - **Published:** August 19, 2026 - **Apply:** https://www.careerboard.com/pt/en/find-jobs-in-United-Kingdom/-91A29DB0E1D7D41A52/ ## About the Role * Significant experience in Data Engineering, Data Platform Engineering, or Data Architecture leadership roles. * Proven experience leading and developing engineering teams. * Strong track record delivering enterprise-scale data platform and data engineering initiatives. * Experience operating within Agile delivery environments. * Excellent stakeholder management and communication skills. * Experience managing multiple priorities within complex organisations. Technical Skills * Microsoft Azure Data Platform technologies, including: * Azure Data Factory (ADF) * Azure Synapse Analytics * Microsoft Fabric * Databricks * Strong SQL and data modelling expertise. * Python and modern data engineering frameworks. * ETL/ELT development and orchestration. * CI/CD pipelines and DevOps practices. * Data monitoring, observability, and operational support. * Cloud-native data architecture and modern data platform design. Desired Attributes * Strong leadership and people management capabilities. * Strategic thinker with a delivery-focused mindset. * Excellent problem-solving and decision-making skills. * Ability to influence senior stakeholders and drive change. * Passion for engineering excellence and continuous improvement. * Strong commercial awareness and business acumen. ## Description We are seeking an experienced Head of Data Engineering to lead the development and delivery of a modern enterprise data platform. This role will be responsible for defining and executing the data engineering strategy, ensuring scalable, secure, and reliable data solutions that support reporting, analytics, machine learning, and AI initiatives. The successful candidate will combine strong technical leadership with hands-on knowledge of modern cloud-based data platforms, data architecture, and engineering best practices. You will work closely with senior stakeholders, architects, analysts, data scientists, and technology teams to deliver business value through high-quality data products and services. Key Responsibilities Data Engineering Leadership * Lead, mentor, and develop a high-performing team of data engineers. * Establish engineering standards, best practices, and ways of working. * Drive a culture of collaboration, accountability, innovation, and continuous improvement. * Support recruitment, onboarding, capability development, and succession planning. Data Platform Strategy & Delivery * Define and execute the data engineering roadmap and platform strategy. * Oversee the design, development, testing, deployment, and support of data pipelines and integrations. * Ensure delivery of scalable, resilient, and secure data solutions aligned with business priorities. * Drive Agile delivery practices and effective backlog management. * Collaborate with business and technical stakeholders to translate requirements into robust technical solutions. Platform Ownership & Operations * Act as the technical owner of the data platform. * Ensure platform availability, scalability, performance, and reliability. * Implement monitoring, alerting, and observability capabilities across data services. * Lead incident management, root cause analysis, and service improvements. * Drive platform optimisation initiatives focused on performance, resilience, and cost efficiency. Data Governance & Quality * Embed data quality controls throughout data pipelines and engineering processes. * Support data governance, security, compliance, and metadata management initiatives. * Ensure appropriate lineage, documentation, and operational standards are maintained. * Partner with business stakeholders to resolve data quality issues and improve data trust. Stakeholder Management * Build strong relationships with senior business and technology stakeholders. * Communicate progress, risks, dependencies, and delivery outcomes effectively. * Provide technical leadership and strategic guidance across data-related initiatives. * Manage relationships with external suppliers and delivery partners where required. Engineering Excellence * Promote automation, reusability, and operational efficiency. * Champion DataOps, DevOps, CI/CD, and infrastructure automation practices. * Contribute to the evolution of enterprise data architecture and engineering standards. * Identify opportunities to improve delivery velocity, platform resilience, and operational effectiveness. ## 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) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) ## Related Articles - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [What Are The Top Skills Required For Azure Developers?](https://www.wearedevelopers.com/magazine/77-what-are-the-top-skills-required-for-azure-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk)