Data Engineering Lead / Data Architect

Weston-super-Mare
2 weeks ago
Create job alert

This rapidly expanding manufacturer and retailer and looking to appoint a Data Engineering Lead / Data Architect to support on the continued evolution their Data Strategy and roadmap towards using more advanced analytics and insight to drive commercial growth. You will be pivotal and hands-on in leading a small team of Data Engineers and BI Developers to support their Cloud transformation.

Client Details

Rapidly expanding manufacturer and retailer

Description

This rapidly expanding manufacturer and retailer and looking to appoint a Data Engineering Lead / Data Architect to support on the continued evolution their Data Strategy and roadmap towards using more advanced analytics and insight to drive commercial growth. You will be pivotal and hands-on in leading a small team of Data Engineers and BI Developers to support their Cloud transformation, a knowledge of Data Architecture is highly desirable but a Senior Data Engineer looking to transition into this domain will also be considered.

Key Responsibilities:

Oversee and lead the design and implementation of ETL/ELT processes to ingest data from new ERP system into Snowflake
Architect and develop the Snowflake data warehouse to support reporting and analytics needs, incorporating existing SQL-Server based business logic, whilst optimising the warehouse structure for performance, scalability, and ease of use
Ensure that the BI and Data team work closely and collaboratively with business users to understand, qualify, design, build test, and deliver their requirements
Work in collaboration with and oversee third-party providers to ensure that technologies and services are both cost-effective and optimized for the organization, while ensuring that providers adhere to established Service Level Agreements.
Provide direction for how the business are moving, transforming, storing, and retrieving data to enable the most efficient and effective use of technology for the business
Design, implement, and manage the BI infrastructure and services, as well as deliver business data insights requirement in alignment to the IT strategy and roadmap
Act as subject matter expert on all aspects of data analytics, analytics data modelling and warehousing, data mining, and presentation with a view to support future relevant projects and initiatives
Ensure that BI service runs smoothly, including to act as a point of escalation for the Support and Technical teams, to monitor and resolve issues
Work with senior stakeholders and programme boards to deliver company KPI reportingKey Technical Areas:

Systems Architecture: Knowledge of system architecture models, including the design, behavior, and interaction of components and subsystems that enable seamless data integration, storage, processing, and analytics, ensuring scalable secure, and efficient solutions aligned with business objectives.
Business Analysis: Translate internal stakeholders'requirements and technology requirements into a strategic application portfolio plan and ensure its effective management and alignment with organisational goals.
Business Intelligence: Knowledge of the data lifecycle from ETL, through to the analysis of datasets, leading to the publication of information and aiding business stake holders to derive insight and potential trends.
IT Security: Understand IT security challenges and risks, and technologies and techniques to mitigate risks.
Effective Governance: Effectively manage projects and programmes including processes, customs and policies that affect these, as well as relationships between stakeholders and company goals.
Service and Supplier Management: The ability to provide high quality Service Management that aligns the delivery of IS services with the needs of the business, through high-quality products services and the management of external services Key Skills & Experience:

Essential:

Experience with ETL/ETL tools (Matillion preferred)
Experience of SQL Server and Snowflake (or other variants of Cloud Data Warehousing solutions e.g Azure / AWS etc)
Experience using Kimball methodology to support analytics and reporting
Experience with data migration, including mapping existing business logic to new data sources
Experience of converting business requirements into a delivered solution
Experience with Power BIDesirable:

Experience of Business Systems reporting, including ERP
Understanding of the MS BI stack (SSIS, SSAS)
Knowledge of Microsoft Dynamics AX or IFS
Manufacturing and supply chain exposure
Understanding of financial principles
Experience of business KPI reporting

Profile

Key Skills & Experience:

Essential:

Experience with ETL/ELT tools (Matillion preferred)
Experience of SQL Server and Snowflake (or other variants of Cloud Data Warehousing solutions e.g Azure / AWS etc)
Experience using Kimball methodology to support analytics and reporting
Experience with data migration, including mapping existing business logic to new data sources
Experience of converting business requirements into a delivered solution
Experience with Power BIDesirable:

Experience of Business Systems reporting, including ERP
Understanding of the MS BI stack (SSIS, SSAS)
Knowledge of Microsoft Dynamics AX or IFS
Manufacturing and supply chain exposure
Understanding of financial principles
Experience of business KPI reportingJob Offer

Opportunity to work on a major Data Transformation Programme

Opportunity to join a rapid growth organisation

Related Jobs

View all jobs

Data Architect - Contract

Senior Data Consultant

Data Engineering Lead - AWS & Snowflake

Lead Data Engineer AWS (London Area)

Data Engineer

New Business Sales Lead – Transportation - Data Engineering / Data Architecture Solutions Business

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Quantum-Enhanced AI in Data Science: Embracing the Next Frontier

Data science has undergone a staggering transformation in the past decade, evolving from a niche academic discipline into a linchpin of modern industry. Across every sector—finance, healthcare, retail, manufacturing—data scientists have become indispensable, leveraging statistical methods and machine learning to turn raw information into actionable insights. Yet as datasets grow ever larger and machine learning models become more computationally expensive, there are genuine questions about how far current methods can be pushed. Enter quantum computing, a nascent but promising technology grounded in the counterintuitive principles of quantum mechanics. Often dismissed just a few years ago as purely experimental, quantum computing is quickly gaining traction as prototypes evolve into cloud-accessible machines. When paired with artificial intelligence—particularly in the realm of data science—the results could be game-changing. From faster model training and complex optimisation to entirely new forms of data analysis, quantum-enhanced AI stands poised to disrupt established practices and create new opportunities. In this article, we will: Explore how data science has reached its current limits in certain areas, and why classical hardware might no longer suffice. Provide an accessible overview of quantum computing concepts and how they differ from classical systems. Examine the potential of quantum-enhanced AI to solve key data science challenges, from data wrangling to advanced machine learning. Highlight real-world applications, emerging job roles, and the skills you need to thrive in this new landscape. Offer actionable steps for data professionals eager to stay ahead of the curve in a rapidly evolving field. Whether you’re a practising data scientist, a student weighing up your future specialisations, or an executive curious about the next technological leap, read on. The quantum era may be closer than you think, and it promises to radically transform the very fabric of data science.

Data Science Jobs at Newly Funded UK Start-ups: Q3 2025 Investment Tracker

Data science has become an indispensable cornerstone of modern business, driving decisions across finance, healthcare, e-commerce, manufacturing, and beyond. As organisations scramble to capitalise on the insights their data can offer, data scientists and machine learning (ML) experts find themselves in ever-higher demand. In the UK, which has cultivated a robust ecosystem of tech innovation and academic excellence, data-driven start-ups continue to blossom—fuelled by venture capital, government grants, and a vibrant talent pool. In this Q3 2025 Investment Tracker, we delve into the newly funded UK start-ups making waves in data science. Beyond celebrating their funding milestones, we’ll explore the job opportunities these investments have created for aspiring and seasoned data scientists alike. Whether you’re interested in advanced analytics, NLP (Natural Language Processing), computer vision, or MLOps, these start-ups might just offer the career leap you’ve been waiting for.

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.