Analytics Engineer

Role Mission

Claranet’s strategy is to build long-term, trusted relationships with its customers by delivering market-leading, integrated managed services. We are seeking a leader to build and to own the existing and future market-leading multi-solutions portfolio that Claranet offers to customers that enables cross and up sell.

Essential Duties and Responsibilities

• You will analyse customer’s existing or proposed platforms to make recommendations on suitable products and data modelling
  
  
• You will translate business requirements into high-level designs and technical specifications
  
  
• You will be able to articulate design decisions to both technical and non-technical stakeholders
  
  
• You will work independently or as part of a larger project team to build new customer environments
  
  About You
  
  Behavioural competencies – Organisational and Behavioural Fit
  
  
• You have a positive mindset: you're excited by unfamiliar challenges and learning new things
  
  
• You're collaborative, supportive, and love to help others learn
  
  
• You believe in shared accountability, celebrating success, and learning from failures
  
  
• You’re an enthusiastic self-starter, eager to learn a wide variety of technologies and apply them to real-world customer problems
  
  
• An understanding of the ethics of gathering and working with data
  
  Critical competencies – Technical Fit
  
  
• Extensive experience with Power BI, with understanding of workspace administration, capacity management, and licensing
  
  
• Strong knowledge of SQL and data warehouse and lakehouse design methodologies (i.e. STAR schema approach and medallion architecture); and experience applying this to real-world data modelling scenarios by developing raw data to create databases, tables, and views for analytics
  
  
• Background working with programming (such as Python and/or R) and scripting languages (e.g. PowerShell) for statistical analysis, automation, and working with APIs
  
  
• Understanding of a variety of approaches to data platforms (e.g. Data Lake, Data Mesh, Data Warehouse, streaming, batch processing)
  
  
• Knowledge of security, GDPR and PII data handling principles
  
  Experience with the following technologies is desirable:
  
  
• Microsoft Fabric and Microsoft Purview
  
  
• Data solutions from one or more of the public cloud providers:
  
  
  • Azure (Azure Synapse Analytics, Azure Data Factory, Azure functions, Azure Databricks, AzureML, Azure AI Services)
    
    
  • AWS (Amazon Redshift, AWS EMR, AWS Glue, AWS Lambda, Amazon Kinesis, AWS SageMaker, Amazon Forecast)
    
    
• Rmarkdown and Shiny Apps
  
  Position Summary
  
  The Analytics Engineer is responsible for:
  
  
• Developing and managing data models to support analytics and reporting
  
  
• Collaborating with data architects, data analysts, data scientists, and business stakeholders to translate customer requirements into technical specifications for ingesting and modelling data
  
  
• Contributing to technical and solution design decisions by providing expert insight into data sources and analytics product features
  
  
• Applying engineering best practices using source control, testing, CI / CD for automated deployment, and monitoring and control mechanisms for DataOps
  
  
• Designing, building, and testing scalable data and analytics pipelines for data ingestion, processing, and storage both programmatically and with low / no-code tools
  
  
• Programmatically analysing customer data and analytics estates and business intelligence tooling using scripts and automated report generation
  
  
• Implementing governance tooling (e.g. Microsoft Purview, Databricks Unity Catalog) for managing access, creating data catalogues, deriving lineage views, and monitoring analytics workloads and infrastructure
  
  
• Creating and maintaining reports and dashboards using BI tools such as Power BI by cleaning, transforming, enriching, and curating data ready for scalable self-service analytics
  
  
• Engineering scalable and repeatable AI solutions using platforms such as Azure AI Service
  
  
• Running scalable and repeatable machine learning experiments, and deploying models into production with automated modelling and deployment with MLOps practices
  
  
• Upskilling customers and colleagues on best practices for data visualisation and keeping up-to-date on new feature releases of new and existing analytics products
  
  Objectives and Key Results
  
  The Analytics Engineer is part of the Data Practice. This team is made up of experts dedicated to Data centric offers (Data platform, Data Analytics, IoT, Big Data, Data compliance) who support our customers in their IT and Data transformations.
  
  We help customers choose the right tools and services, build highly scalable secure environments, and help them manage the maintenance of those environments. We come up with creative solutions to difficult problems and every engineer gets to have a large direct impact on each of those customers.
  
  The team is made up of engineers from all around the country in distributed teams. You can work fully remote or at any Claranet UK office – most people choose a combination of the two. We’ve worked hard to create a remote-friendly culture and believe you can have a big impact no matter where you live.
  
  Working in the Data Practice we can offer an environment where you will be surrounded by like-minded, highly technical people. Due to the nature of our business, interesting projects and the possibility to learn and use new technologies are commonplace. We want you to develop and grow as our organization does