Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Solutions Architect

Data Intellect
Belfast
9 months ago
Applications closed

Related Jobs

View all jobs

Solutions Architect - Big Data and DevOps (f/m/d)

Data Architect...

Professional Services Manager (Data Engineering Team)

AWS Data Architect

Data Architect - Azure

Data Architect

Job Description

As a Solutions Architect at [DI] you will work on a variety of impactful customer technical projects, including designing and building reference architectures and productionalising customer use cases within Capital Markets.

What you will be doing:

  • Define end-to-end data architectures, ensuring best practices for data governance, access control, and cost optimisation using Unity Catalog and Delta Lake 
  • Provide guidance on Databricks best practices for query performance tuning, storage optimisation, and efficient compute resource allocation
  • Guide strategic customers in adopting Databricks Lakehouse as a unified data platform for structured and unstructured market data
  • Enhance and grow your knowledge among subject matter experts in our learning and development ecosystem


Qualifications

  • Proficient in data engineering, data platforms and analytics
  • Deep experience with Python, SQL and/or Scala
  • Knowledge of two or more common Cloud ecosystems (Azure, AWS, GCP) with expertise in at least one.
  • Deep experience with distributed computing with Apache Spark
  • Working knowledge CI/CD for production deployments
  • Working knowledge of MLOps
  • Familiarity with designing and deploying performant end-to-end data architectures
  • Experience with technical project delivery, managing scope and timelines
  • Able to communicate complex technical concepts to business stakeholders
  • Adaptable to evolving technologies and projects
  • At least one Databricks Certification, Data or ML Engineering.



Additional Information

What we offer: 

  • Flexible working – we offer hybrid working so our people can achieve that elusive work/life balance.
  • Professional development – we offer extensive training, ranging from leadership to specific technical skills.
  • Progression opportunities - we run a biannual promotion process. Monthly 121s with your People Leader provides support to guide you and your career in the right direction.
  • International travel opportunities – we offer the opportunity to work internationally, with teams in Belfast, London, New York, Hong Kong & Singapore
  • Healthcare cover – provider is dependent on region, UK is provided by Benenden Health, including 24/7 GP Service & Mental Health Helpline to give you peace of mind when it comes to your health
  • Generous referral scheme – we love to see referrals and referring a friend means cash for you!
  • Regular social events, prizes and giveaways – our talented social committee work hard all year round to provide exciting events across all regions to promote our value of togetherness

Who We Are:

Simply put – we turn big data problems into smart data solutions.

Data Intellect is a leading data and technology consultancy specializing in creating cutting-edge financial and capital markets technology solutions. Our expertise extends to diverse industries, including smart energy and healthcare.

Fair employment and equal opportunities

Data Intellect is an equal opportunity employer, committed to inclusion and diversity.

If you have a disability, accommodations are available on request throughout the assessment and selection processes.

Ready to accept the challenge?

Apply now.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.