Reports to: Engineering Manager

Join Our Mission

At QuantSpark, we're transforming how data and AI serve society. Our team partners with forward-thinking organisations across multiple sectors to harness the power of analytics and artificial intelligence, creating meaningful impact that extends far beyond financial outcomes.

Our impressive client portfolio:

• Private Equity & Financial Services: We work with top-tier investment firms, global financial institutions, and leading wealth management companies, providing portfolio performance analytics, AI-powered value creation, and risk identification tools.
• Retail & Consumer: Our solutions help major national retailers, high-street brands, and premium consumer goods companies optimise inventory, enhance price competitiveness, and deliver personalised customer experiences.
• Asset Management: We build AI-powered investment decision support systems, alternative data integration platforms, and automated risk management solutions for prestigious asset management firms.
• Public Sector: We're trusted by multiple UK government departments and public sector organisations to deliver predictive maintenance systems, supply chain optimisation, and process automation.
  SaaS, Manufacturing & More: From innovative SaaS providers to global manufacturing leaders, our cross-industry expertise ensures we bring diverse perspectives to complex challenges.

We're looking for Data Engineers at Mid and Senior level who are passionate about turning complex data into actionable insights that drive remarkable results for our clients.

Why this role will accelerate your career

We know that at this stage of your career, the right environment matters as much as the role itself. Here's what that looks like at QuantSpark:

Real career growth: Our last hire at this level moved to Senior Data Engineer within 18 months. It reflects the pace at which people develop when they're working across varied, complex client problems rather than maintaining a single internal stack.
Training budget that you'll actually use: We invest £6,000 per person per year in learning and development and we mean it. People use it for master's degrees, industry conferences, and professional certifications.
Client exposure from day one: In your first year you'll work across multiple client engagements spanning FTSE 100 companies, PE-backed portfolio businesses, and government departments. The breadth of exposure you'll get here could take five years or more to accumulate in a single in-house role.
Mentorship that's built in: You'll work alongside talented senior engineers who are invested in your development; technically and in how you navigate client relationships.

The Real Challenges You'll Help Us Solve

We believe in being upfront about what joining a scale-up consultancy actually looks like:

• Messy data: Real client data is rarely clean. You'll need creativity and rigour to build pipelines that handle edge cases, missing data, and evolving schemas.
• Varied stacks: Each client brings different tools and constraints. Adaptability matters more than knowing every platform in advance.
• Building while flying: We're still maturing some of our data engineering standards. You'll help shape them, which is an opportunity as much as an ambiguity.
• Speed vs. quality: Clients need results quickly, and our reputation depends on delivering robustly. Holding that balance is a skill we'll help you develop.

If that sounds energising, you'll fit in well here.

Role Requirements

This isn't a graduate role, so to succeed you'll need real production experience. But you don't need to have done it all independently yet. We're looking for someone with strong foundations who is ready to grow quickly with the right support around them.

Technical

• Circa 3 years of experience in data engineering, analytics engineering, or a closely related role, with hands-on exposure to production environments
• Competency with SQL across multiple database platforms
• Python proficiency for data manipulation and pipeline work (Pandas, SQLAlchemy)
• Hands-on experience with cloud data warehouses (Snowflake, BigQuery, or Redshift)
• Familiarity with data modelling concepts and ELT/ETL design patterns

Skills & Approach

• Clear communicator: comfortable explaining technical concepts to non-technical stakeholders
• Collaborative and reliable in cross-functional teams
• Organised enough to manage multiple workstreams without things falling through the cracks
• Curious and keen to keep developing: data engineering is a fast-moving space

What Success Looks Like in Your First Year

• Technical Impact: Successfully contribute to data and analytics engineering projects, delivering robust data pipelines that drive measurable business outcomes for clients
• Quality Leadership: Utilise data quality frameworks and testing practices that become standard across our engineering teams
• Client Relationships: Interact with key technical stakeholders at major clients, becoming a trusted contributor to their data strategy outcomes
• Innovation Contribution: Research and evaluate new tools, practices, or methodologies that improve our team's efficiency and solution quality

Benefits

• £6,000 annual training & conference budget
• Up to 6% matched pension for your long-term security
• Comprehensive private healthcare through Vitality
• Work from anywhere in the world for up to 20 days per year
• 25 days holiday + bank holidays + flexibility to buy/sell up to 5 additional days
• Sustainable commuting support through our cycle to work scheme
• Engaging Central London office environment with quality refreshments, regular team socials, and a vibrant atmosphere
• Exclusive discounts on retail, travel, technology, and fitness memberships
• Regular tech talks, knowledge sharing sessions, and innovation time
• Internal Tech mentorship program