

Bounteous
Data Engineer
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Engineer with 5-7 years of experience, specializing in Snowflake and/or Databricks. Remote work available; requires expertise in data science, analytics, and project management across Banking, Insurance, and Consultancy sectors. Advanced quantitative degree needed.
π - Country
United Kingdom
π± - Currency
Β£ GBP
-
π° - Day rate
Unknown
-
ποΈ - Date
November 13, 2025
π - Duration
Unknown
-
ποΈ - Location
Remote
-
π - Contract
Unknown
-
π - Security
Unknown
-
π - Location detailed
Glasgow, Scotland, United Kingdom
-
π§ - Skills detailed
#Deployment #Cloud #Compliance #ML (Machine Learning) #Trend Analysis #A/B Testing #Leadership #Data Engineering #Project Management #Mathematics #Scala #Data Quality #Tableau #Data Integration #Snowflake #GCP (Google Cloud Platform) #Microsoft Power BI #Business Analysis #Data Visualisation #SQL (Structured Query Language) #SAS #Python #Datasets #Monitoring #Data Science #BI (Business Intelligence) #Alteryx #Databricks #Data Architecture
Role description
Senior Data Architect/Engineer
Location: Glasgow, UK or Anywhere in UK
Experience: Minimum of 5 - 7 years of experience
Snowflake and/or databricks is must - hands on experience
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 βwhat-ifβ 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 5 - 7 years of experience in data science, analytics, operational research or a related field.
β’ Snowflake and/or databricks is must - hands on experience
β’ Advanced degree in a quantitative field (e.g. Data Science, Engineering, Mathematics, etc.)
Senior Data Architect/Engineer
Location: Glasgow, UK or Anywhere in UK
Experience: Minimum of 5 - 7 years of experience
Snowflake and/or databricks is must - hands on experience
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 βwhat-ifβ 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 5 - 7 years of experience in data science, analytics, operational research or a related field.
β’ Snowflake and/or databricks is must - hands on experience
β’ Advanced degree in a quantitative field (e.g. Data Science, Engineering, Mathematics, etc.)






