Systems Engineer

Business Partnering and Requirements Gathering
•      Work with business stakeholders to understand reporting needs, business objectives, and decision-making requirements.
•      Support requirements discovery sessions, stakeholder workshops, and report design reviews.
•      Translate business requirements into clear BI specifications, including KPIs, metrics, dimensions, and data definitions.
•      Ask clarifying questions to ensure BI solutions address the true business need rather than simply recreating existing manual reports.
•      Support prioritization of BI requests in collaboration with senior team members.
BI Solution Design and Delivery
•      Design and develop Power BI reports, dashboards, datasets, and semantic models for defined business requirements.
•      Build clear, performant, and well-structured Power BI solutions that support operational and tactical decision-making.
•      Apply DAX, Power Query, data modelling, and report optimisation techniques.
•      Take ownership of small-to-medium reporting solutions from design through deployment and support.
•      Apply established design patterns, templates, and reusable components to improve consistency.
•      Support the review and improvement of existing Power BI solutions.
Data Engineering
•      Build and maintain data pipelines using Azure Databricks, Azure Synapse Analytics, Synapse Link, or Microsoft Fabric.
•      Write and troubleshoot SQL to extract, validate, and reconcile data from source systems.
•      Use Python and PySpark for data transformation and pipeline development tasks.
•      Support source-to-target mapping, data validation, and data quality checks.
•      Follow source control practices (Git) and contribute to CI/CD deployment processes for data and BI assets.
Standards, Documentation and Governance
•      Follow agreed BI and data engineering standards, naming conventions, and development practices.
•      Maintain clear documentation for reports, datasets, data definitions, and pipelines.
•      Support workspace and dataset governance, including certified datasets and access management.
•      Identify data quality or process issues and escalate them for resolution.
User Support and Adoption
•      Provide day-to-day support for Power BI reports, dashboards, and datasets.
•      Help users navigate reports, interpret KPIs, and apply filters or drill-throughs.
•      Create and maintain user guides, data dictionaries, and training materials.
•      Troubleshoot report, data, and refresh issues, escalating complex cases to senior team members.
Required Skills and Experience
•      Bachelor’s degree in a related field, or an equivalent combination of education and directly relevant experience.
•      Hands-on experience designing and building data pipelines using Azure data engineering technologies, such as Azure Databricks, Azure Synapse Analytics, Synapse Link, or Microsoft Fabric.
•      Experience using Python and PySpark within Azure Databricks or Synapse Spark pools for data transformation and notebook-based workflows.
•      Working knowledge of source control with Git and exposure to CI/CD or automated deployment practices.
•      Solid experience developing Power BI reports, dashboards, and datasets, including DAX, Power Query, and data modelling.
•      Strong SQL skills, including the ability to query, validate, and troubleshoot datasets.
•      Understanding of modern data architecture patterns, including medallion architecture, lakehouse design, and Delta Lake.
•      Good understanding of data visualization and dashboard design principles.
•      Good communication and stakeholder engagement skills.
•      Ability to manage own workload across data engineering and BI tasks and deliver to agreed deadlines.
•      Ability to work effectively as part of a global Data & Analytics team.
Preferred Skills and Experience
•      Experience in manufacturing, engineering, industrial, or global operational environments.
•      Experience working with ERP, CRM, finance, supply chain, sales, service, manufacturing, or operational data.
•      Exposure to Power BI deployment pipelines, row-level security, or workspace governance.
•      Familiarity with Agile delivery methods, backlog management, and iterative analytics delivery.
•      Understanding of master data, data cataloguing, and metadata management.
•      Interest in developing toward a senior data engineering or BI leadership role.