Senior Azure Data Engineer

Mission/Purpose of the Job (one or two sentences that sum up the reason the job is needed): Info The Engineer develops technology capabilities and services that Product teams use to build customer-facing solutions, expediting the delivery of technology-enabled value to the Business. They develop and/or configure technologies to meet technical requirements and architecture, whilst ensuring the services they build are robust, maintainable, reusable, and highly scalable. Engineer has ownership of end-to-end data pipelines (semantic layer -> bespoke layer), do architectural decision within Azure Data Platform, owns non-functional requirements such as performance improvement, cost reduction and security standards, providing long-term technical direction for data engineering within Product Team. Skills / Knowledge / Experience Mandatory Proven track record of independently delivering and owning highquality, secure, and scalable technology solutions that meet complex functional and nonfunctional requirements within modern Azurebased data architectures. Mandatory Advanced experience with endtoend solution quality assurance, including data validation, automated testing strategies, performance testing, and production readiness to ensure longterm scalability, reliability, and maintainability. Mandatory Deep, handson expertise in the Azure Data Platform, including design, development, and operation of data pipelines and platforms using technologies such as
Azure Data Factory,
Databricks,
Delta Lake,
Snowflake, and
related Azure services. Mandatory Strong experience designing and applying DevOps and DataOps practices for data platforms, including
CI/CD pipelines,
infrastructureascode,
automated testing,
deployment,
monitoring, and
release management (e.g., Azure DevOps, Jenkins, Gitbased workflows). Mandatory Strong understanding of software engineering principles, cloud architecture, information risk, data security, and governance, with the ability to apply these principles pragmatically in complex, enterprisescale environments. Mandatory Extensive handson experience in modern programming and scripting languages commonly used in data engineering (e.g., Python, SQL, PySpark; additional languages such as Java or .NET beneficial), with a strong focus on readable, maintainable, and performant code. Mandatory Recognised seniorlevel engineering expertise in data engineering and cloud platforms, demonstrated through successful ownership of production systems, architectural decisionmaking, mentoring of other engineers, and, where applicable, relevant professional certifications (e.g., Azure Data Engineer, Cloud Solution Architect). Mandatory Experience working effectively across Agile and hybrid delivery models, including Agile (e.g., Kanban / Scrum) and Waterfall environments, with the ability to influence engineering practices and continuously improve ways of working. Mandatory Strong analytical and problemsolving skills, with the ability to assess tradeoffs (cost, performance, complexity, risk), make sound technical decisions, and clearly communicate reasoning to both technical and nontechnical stakeholders. Mandatory AIaware data engineering mindset, with practical understanding of how Azure data platforms enable machine learning and generative AI workloads (e.g. data preparation for ML, feature engineering, model serving integration, and consumption of AI outputs within data solutions). Mandatory Experience or working knowledge of Azure AIrelated services (e.g. Azure Machine Learning, Azure OpenAI, Cognitive Services) and how they integrate with Azure Data Platform components, without being responsible for data science or model development Key Responsibilities : Main Responsibilities (Give 6 to 8 main areas of work. State what is to be done –to what - the end result e.g. Develop, agree and implement detailed sales plans to increase market share in Europe): Must Have: Designs, configures, develops, builds, tests, and releases endtoend Azurebased data solutions and services that meet functional and nonfunctional requirements, contributing to the delivery of highvalue, scalable Product increments. Must Have: Leads the design and implementation of data engineering solutions and architectural components across the Azure Data Platform (e.g., Azure Data Factory, Databricks, Snowflake, SAP BW, MuleSoft, Apigee), ensuring alignment with enterprise architecture standards and best practices. Must Have: Acts as a technical authority for data engineering, collaborating closely with Product Owners, Platform Owners, Platform Architects, and stakeholders to translate business requirements into robust, maintainable, and costefficient data solutions. Must Have: Owns complex incidents, defects, and escalations, identifying root causes and driving sustainable fixes across data pipelines, platforms, and integrations. Must Have: Delivers secure, highquality, productiongrade code, ensuring compliance with security, data governance, and engineering standards, and proactively addressing performance, reliability, and scalability concerns. Must Have: Proactively identifies and drives resolution of technical debt, makes independent technical decisions, clearly communicates tradeoffs (e.g. cost, performance, complexity), and serves as the primary point of contact for data engineering topics within the Product or Platform area. Must Have: Defines and enforces data engineering standards and best practices, including data modelling approaches, coding standards, CI/CD patterns, monitoring, and documentation to support longterm platform sustainability. Must Have: Mentors and supports other engineers, providing technical guidance, design and code reviews, and knowledge sharing to raise overall data engineering maturity within the team. Must Have: Documents architectures, solutions, and operational procedures to ensure maintainability, supportability, and effective handover across teams. Must Have: Applies Agile principles and ways of working to efficiently design, deliver, and continuously improve data solutions (e.g., Kanban), while influencing ways of working through experience and continuous improvement initiatives. Must Have: Drives a culture of continuous improvement, actively contributing to enhancements in data platform stability, performance, observability, and cost optimisation. Must Have: Supports and fulfils advanced Product and Platform service requests, such as access strategy, solution insights, data quality investigations, and platform optimisation activities. Scope of the job (give details of nature and scope of role) Info: The Senior Azure Data Engineer contributes to the development and evolution of Product capabilities and data platform services by designing, owning, and delivering highquality, secure, and scalable Azurebased data solutions. The role covers the full lifecycle of data solutions, from design and implementation through testing, release, and production operation. Info: The Senior Azure Data Engineer fulfils complex and evolving technical requirements and architectures by selecting, designing, and actively developing relevant Azure Data Platform technologies. They take endtoend technical ownership of data pipelines and platforms, ensuring that solutions are robust, maintainable, performant, and aligned with enterprise architecture, security, and data governance standards. Info: The Senior Azure Data Engineer is AIaware from an Azure data platform perspective, ensuring that data architectures, pipelines, and platforms are designed to effectively support analytics, machine learning, and generative AI use cases (e.g. integration with Azure Machine Learning, Azure OpenAI, feature stores, and model consumption patterns), while maintaining strong governance, security, and cost control. Info: Working closely with the Product Owner and Product Solution Architect, the Senior Azure Data Engineer proactively identifies, prioritises, and remediates technical debt, makes independent technical decisions, and drives continuous improvements to the efficiency, reliability, and effectiveness of the data platform and delivered solutions. Info: The role also includes acting as a technical authority for data engineering, supporting and mentoring other engineers, contributing to architectural discussions, and ensuring engineering best practices are consistently applied across delivered solutions. Info: The Senior Azure Data Engineer reports to the Product Owner.