Data Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
🌎 - Country
United Kingdom
πŸ’± - Currency
Β£ GBP
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πŸ’° - Day rate
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πŸ—“οΈ - Date discovered
September 16, 2025
πŸ•’ - Project duration
More than 6 months
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🏝️ - Location type
Remote
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πŸ“„ - Contract type
Fixed Term
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πŸ”’ - Security clearance
Unknown
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πŸ“ - Location detailed
Glasgow, Scotland, United Kingdom
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🧠 - Skills detailed
#Deployment #SQL (Structured Query Language) #Data Architecture #Python #Tableau #Business Analysis #Data Visualisation #Cloud #Trend Analysis #Data Science #Mathematics #GCP (Google Cloud Platform) #Project Management #Data Integration #Data Quality #ML (Machine Learning) #SAS #BI (Business Intelligence) #Datasets #Microsoft Power BI #A/B Testing #Leadership #Monitoring #Scala #Alteryx #Data Engineering #Compliance
Role description
Senior Data Architect/Engineer Location: Glasgow, UK or Anywhere in UK Duration Required: β€’ 6 months to start with in a contract capacity. This role will be key to helping our divisional leadership to making informed, data-driven decisions by developing a sophisticated, scalable and explainable decision model to aid workforce planning. The ideal candidate will have deep expertise in data science, analytics and systems thinking, with a proven ability to work across different businesses. This is a high-impact role with the work output to be visible at the executive level. Key Responsibilities: Design & Architecture: Lead design for decision support model from formation through to deployment. Define model framework that balances predictive accuracy with interoperability and useability. Data Integration & Engineering: Partner with other teams responsible for datasets required to be leveraged so it can be sourced, cleansed, and prepared into a structured format, where possible. Model Development: Apply statistical, machine learning or optimization techniques to develop a robust decision support system. Simulate scenarios, perform sensitivity analysis, and create β€œwhat-if” tools for stakeholders. Business Analysis: Translate business requirements into analytic frameworks and technical solutions. Work closely with business stakeholders to ensure the model aligns with strategic goals and operational needs. Data Visualisation & Communication: Build dashboards, reports or interactive tools that clearly communicate model outputs and decision recommendations for executive levels. Governance & Monitoring: align with governance practices including model risk management, validation, versioning, performance tracking and recalibration. Establish KPIs to measure the impact of the model on decision quality and business outcomes. Key Skills Desired: β€’ Data Modelling: Ability to build a methodology with statistical techniques and then scale and automate. β€’ Industry Expertise : Demonstrated experience across diverse sectors including Banking, Insurance, and Consultancy, focusing on Data Analytics and Data Insights. β€’ Stakeholder Engagement : Adept at translating analytical findings into actionable insights for various stakeholders, ensuring stakeholder centric outcomes. β€’ Project Management : Proficient in managing end- to- end analytics projects, leading initiatives to explore customer journeys, and data to drive business decisions. β€’ Technical Proficiency : Skilled in SQL, Google Cloud Platform Big Query, Adobe Analytics, Tableau, Power BI, and Python, delivering data- driven recommendations and ensuring data quality in projects. β€’ Commercial Analytics : Engaged in projects to understand impact on revenue, automated reporting, and improved efficiency using SQL, SAS, and Alteryx. β€’ Data Quality and Governance : Ensured compliance with regulatory guidelines and addressed data gaps. β€’ Regulatory Compliance and Reporting : Supported creation of dashboards & reporting, liaising with stakeholders and managing ad hoc MI requests. β€’ Project Exposure: Performed profiling and trend analysis, analysis of large complex datasets to support decision- making, A/B testing, measurement of impact on commercial outcomes, impact analysis, performance analysis, identification of remediation issues involving data. Qualifications: β€’ Experience: Minimum of 15 years of experience in data science, analytics, operational research or a related field. β€’ Advanced degree in a quantitative field (e.g. Data Science, Engineering, Mathematics, etc.)