Data Architect

Version 1
Belfast
1 month ago
Applications closed

Related Jobs

View all jobs

Data Architect

Data Architect

Data Architect

Data Architect

Data Architect

Data Architect Manager

Job Description

As a Data Solution Architect you will be expected to take an architecture lead role on our client’s solution delivery engagements, with high levels of customer engagement. This will involve ongoing analysis of business requirements throughout the lifetime of the service. Candidates will have a strong understanding of data architecture and analytics design and project delivery life-cycles with an emphasis of working in client facing environments.

Typically the role will involve the following:

  • Translating Business requirements to technical solutions and the production of specifications,
  • Designing and implementing business intelligence & modern data analytics platform technical solutions,
  • Data architecture design and implementation
  • Data modelling,
  • ETL, data integration and data
  • migration design and implementation
  • Master data management system and process design and implementation,
  • Data quality system and process design and implementation,
  • Major focus on data science, data visualisation, AI, ML,
  • Documentation of solutions (e.g. data modelling, configuration, and setup etc.) including HLD and LLD,
  • Working within a project management/agile delivery methodology,
  • Managing Team Members on a day to day basis,
  • Managing technical delivery of solution,
  • Strong stakeholder management and communication ski


Qualifications

  • Hands on experience with data solution architecture, design and rollout.
  • Hands on experience with business intelligence tools, data modelling, data staging, and data extraction processes, including data warehouse and cloud infrastructure.
  • Experience with multi-dimensional design, star schemas, facts and dimensions. 
  • Experience and demonstrated competencies in ETL development techniques.
  • Experience in data warehouse performance optimization.
  • Experience on projects across a variety of industry sectors an advantage,
  • Comprehensive understanding of data management best practices including demonstrated experience with data profiling, sourcing, and cleansing routines utilizing typical data quality functions involving standardization, transformation, rationalization, linking and matching,
  • Good knowledge of Databricks, Snowflake, Azure / AxoWS / Oracle cloud, R, Python. 



Additional Information

At Version 1, we believe in providing our employees with a comprehensive benefits package that prioritises their well-being, professional growth, and financial stability.

One of our standout advantages is the ability to work with a hybrid schedule along with business travel, allowing our employees to strike a balance between work and life. We also offer a range of tech-related benefits, including an innovative Tech Scheme to help keep our team members up-to-date with the latest technology.

We prioritise the health and safety of our employees, providing private medical and life insurance coverage, as well as free eye tests and contributions towards glasses. Our team members can also stay ahead of the curve with incentivized certifications and accreditations, including AWS, Microsoft, Oracle, and Red Hat.

Our employee-designed Profit Share scheme divides a portion of our company's profits each quarter amongst employees. We are dedicated to helping our employees reach their full potential, offering Pathways Career Development Quarterly, a programme designed to support professional growth.

Laura Cowan

#LI-LC1

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.

Careers Jobs

Top 10 Books to Advance Your Machine Learning Career in the UK

Machine learning (ML) remains one of the fastest-growing fields within technology, reshaping industries across the UK from finance and healthcare to e-commerce, telecommunications, and beyond. With increasing demand for ML specialists, job seekers who continually update their knowledge and skills hold a significant advantage. In this article, we've curated ten essential books every machine learning professional or aspiring ML engineer in the UK should read. Covering foundational theory, practical implementations, advanced techniques, and industry trends, these resources will equip you to excel in your machine learning career.

Careers

Navigating Machine Learning Career Fairs Like a Pro: Preparing Your Pitch, Questions to Ask, and Follow-Up Strategies to Stand Out

Machine learning (ML) has swiftly become one of the most in-demand skill areas across industries, with companies leveraging predictive models and data-driven insights to solve challenges in healthcare, finance, retail, manufacturing, and beyond. Whether you’re an early-career data scientist aiming to break into ML, a seasoned engineer branching into deep learning, or a product manager exploring AI-driven solutions, machine learning career fairs offer a powerful route to connect with prospective employers face-to-face. Attending these events can help you: Network with hiring managers and technical leads who make direct recruitment decisions. Gain insider insights on the latest ML trends and tools. Learn about emerging job roles and new industry verticals adopting machine learning. Showcase your interpersonal and communication skills, both of which are increasingly important in collaborative AI/ML environments. However, with many applicants vying for attention in a bustling hall, standing out isn’t always easy. In this detailed guide, we’ll walk you through how to prepare meticulously, pitch yourself confidently, ask relevant questions, and follow up effectively to land the machine learning opportunity that aligns with your ambitions.

Jobs

Common Pitfalls Machine Learning Job Seekers Face and How to Avoid Them

Machine learning has emerged as one of the most sought-after fields in technology, with companies across industries—from retail and healthcare to finance and manufacturing—embracing data-driven solutions at an unprecedented pace. In the UK, the demand for skilled ML professionals continues to soar, and opportunities in this domain are abundant. Yet, amid this growing market, competition for machine learning jobs can be fierce. Prospective employers set a high bar: they seek candidates with not just theoretical understanding, but also strong practical skills, business sense, and an aptitude for effective communication. Whether you’re a recent graduate, a data scientist transitioning into machine learning, or a seasoned developer pivoting your career, it’s essential to avoid common mistakes that may hinder your prospects. This blog post explores the pitfalls frequently encountered by machine learning job seekers, and offers actionable guidance on how to steer clear of them. If you’re looking for roles in this thriving sector, don’t forget to check out Machine Learning Jobs for the latest vacancies across the UK. In this article, we’ll break down these pitfalls to help you refine your approach in applications, interviews, and career development. By taking on board these insights, you can significantly enhance your employability, stand out from the competition, and secure a rewarding position in the world of machine learning.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.