Future Tech Jobs Future Tech Jobs

Solutions Architect (Data Analytics)

Vallum Associates
Slough, England
11 months ago
Applications closed

Related Jobs

View all jobs

Solutions Architect

Synthesia New York City, New York, United States
£140,000 – £230,000 pa Hybrid

Solutions Architect (Retail/CPG)

Databricks London, United Kingdom

Senior Solutions Architect - AI/BI

Databricks London, United Kingdom

Lead Solutions Architect (Digital Natives Business)

Databricks London, United Kingdom

Senior Solutions Architect - Lakewatch

Databricks London, United Kingdom

Senior Solutions Architect (Utilities/Energy)

Databricks London, United Kingdom
Posted
1 Jul 2025 (11 months ago)
Share
Save job
Create job alert

Responsibilities:

  • 16-18+ years of total experience in DWBI, Big Data, Cloud Technologies
  • Implementation experience and hands on experience in either of the 2 Cloud technologies – Azure, AWS, GCP, Snowflake, Databricks
  • Must Have Hands on experience on at least 2 Hyperscalers (GCP/AWS/Azure platforms) and specifically in Big Data processing services (Apache Spark, Beam or equivalent).
  • In-depth knowledge on key technologies like Big Query/Redshift/Synapse/Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF etc.
  • Excellent consulting experience and ability to design and build solutions, actively contribute to RfP response.
  • Ability to be a SPOC for all technical discussions across industry groups.
  • Excellent design experience, with entrepreneurship skills to own and lead solutions for clients
  • Excellent ETL skills, Data Modeling Skills
  • Excellent communication skills
  • Ability to define the monitoring, alerting, deployment strategies for various services.
  • Experience providing solution for resiliency, fail over, monitoring etc.
  • Good to have working knowledge of Jenkins, Terraform, StackDriver or any other DevOps tools.
  • Design and implement effective database solutions and models to store and retrieve data.
  • Examine and identify database structural necessities by evaluating client operations, applications, and programming.
  • Ability to articulate and write POVs on new and old technologies
  • Ability to recommend solutions to improve new and existing database systems.
  • Assess data implementation procedures to ensure they comply with internal and external regulations.
  • Install and organize information systems to guarantee functionality.
  • Prepare accurate database design and architecture reports for management and executive teams.
  • Oversee the migration of data from legacy systems to new solutions.
  • Educate staff members through training and individual support.
  • Offer support by responding to system problems in a timely manner.

Requirements:

  • Strong knowledge of database structure systems and data mining.
  • Knowledge of systems development, including system development life cycle, project management approaches and requirements, design and testing techniques
  • Proficiency in data modeling and design, including SQL development and database administration
  • Ability to implement common data management and reporting technologies, as well as the Columnar and NoSQL databases, data visualization, unstructured data, and predictive analytics.
  • Excellent organizational and analytical abilities.
  • Outstanding problem solver.
  • Good written and verbal communication skills.
  • A minimum of 5 years’ experience in a similar role.
  • Ability to lead and mentor the architects.
  • Mandatory Skills [at least 2 Hyperscalers]
  • GCP, AWS, Azure, Big data, Apache spark, beam on BigQuery/Redshift/Synapse, Pub Sub/Kinesis/MQ/Event Hubs, Kafka Dataflow/Airflow/ADF
  • Desirable Skills
  • Designing Databricks based solutions for Azure/AWS, Jenkins, Terraform, StackDriver or any other DevOps tools

Industry Insights

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

Products

Where to Advertise Data Science Jobs in the UK (2026 Guide)

Advertising data science jobs in the UK requires a different approach to most technical hiring. Data science spans a broad and often misunderstood spectrum — from statistical modelling and experimental design through to machine learning engineering, product analytics and AI research. The strongest candidates identify firmly with specific subdisciplines and are frustrated by adverts that conflate data scientist with data analyst, business intelligence developer or machine learning engineer. General job boards produce high application volumes for data roles but consistently fail to match specialist data science profiles with the right opportunities. This guide, published by DataScienceJobs.co.uk, covers where to advertise data science roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.

Jobs

Data Science Jobs UK 2026: What to Expect Over the Next 3 Years

Data science has spent the past decade being described as the sexiest job of the twenty-first century. By 2026, the reality is both more nuanced and more interesting than that label ever suggested. The discipline has matured, fragmented, deepened, and in some respects reinvented itself — and the jobs market has changed with it in ways that create genuine opportunity for those who understand what employers actually want, and genuine difficulty for those still operating on assumptions formed five years ago. The data science jobs market of 2026 is not simply a larger version of what it was three years ago. The generalist data scientist — equally comfortable wrangling data, building models, and presenting insights to the board — is giving way to a more specialised landscape where employers know exactly what problem they are trying to solve and are looking for candidates with the specific depth to solve it. Machine learning engineering, causal inference, experimentation, AI product development, and domain-specific applied science have all emerged as distinct career tracks within what was previously a single, loosely defined profession. At the same time, the arrival of large language models and the broader AI capability wave has both threatened and created data science roles in equal measure. Some of the work that junior data scientists spent their early careers doing — data cleaning, exploratory analysis, basic model building — is being partially automated by AI tooling. But the demand for practitioners who can evaluate AI systems rigorously, apply statistical thinking to complex business problems, and build the data foundations on which AI depends has grown considerably. The candidates who will thrive over the next three years are those who understand where the discipline is heading — which specialisms are attracting the most investment, which technologies are reshaping what data scientists are expected to build and know, and how to position a data science career that will remain valuable as the field continues to evolve around them. This article breaks down what the UK data science jobs market is likely to look like through to 2028 — covering the titles emerging right now, the technologies driving employer demand, the skills that will matter most, and how to position your career ahead of the curve.

Jobs

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

🍪 Basic, anonymous analytics (aggregate counts only, never shared) are always on. Accept to also enable third-party tools — Google Analytics, Microsoft Clarity, Mixpanel, Leadfeeder — which help us match you with relevant Data Science roles. We never sell your data or use it for cross-site advertising. See our Cookie Policy.