Analytics Engineer , QuantSpark

• 2+ years of experience in analytics engineering, data engineering, or similar roles with substantial experience building production data pipelines
• Python skills (NumPy, Pandas, SQL Alchemy) and expert-level SQL across multiple database platforms
• Hands-on experience with modern data stack tools including dbt, Airflow, and cloud data warehouses (Snowflake, BigQuery, Redshift)
• Strong understanding of data modelling, schema design, and building maintainable ELT/ETL pipelines
• Experience with cloud platforms (AWS, Azure, GCP) and infrastructure-as-code practices
• Familiarity with data visualisation tools (Tableau, PowerBI, Looker) and analytics frameworks
• Proven experience leading technical work streams and mentoring junior team members
• Exceptional communication skills with ability to explain complex technical concepts to both technical and non-technical stakeholders
• Experience working directly with clients or business stakeholders to gather requirements and present solutions
• Strong project management skills with ability to balance multiple priorities and deliver on time
• Collaborative mindset with experience working in cross-functional teams

Desirable

• Reports to: Engineering Manager
• We're seeking an experienced Analytics Engineer who's passionate about turning complex data into actionable insights that drive remarkable results for our clients
• Work That Matters: Lead high-impact analytics projects across diverse sectors—from building predictive models that help private equity firms identify value creation opportunities to creating inventory optimisation algorithms for household-name retailers.Tackle Exciting Challenges: Design and implement technically sophisticated solutions such as real-time analytics platforms for FTSE 100 companies, automated risk assessment systems for asset managers, and predictive maintenance pipelines for government departments
• Build Solutions That Scale: Your analytics engineering will power data products used by millions of customers, from recommendation engines for major retailers to fraud detection systems for financial institutions
• Shape Technical Standards: As a growing consultancy, you'll help define our analytics engineering practices, tooling choices, and data architecture patterns that will serve as the foundation for our continued growth
• Work Alongside Brilliant Minds: Collaborate with exceptionally talented colleagues who bring diverse expertise from leading universities, top tech companies, and varied industry backgrounds—all united by intellectual curiosity and a drive to solve meaningful problems
• Lead Technical Delivery: Own end-to-end technical execution of analytics projects, from initial data exploration through to production deployment. You'll architect robust data pipelines that transform messy real-world data into reliable, business-ready datasets
• Drive Data Excellence: Champion analytics engineering best practices, implementing automated testing frameworks, data quality monitoring, and documentation standards that ensure our solutions are production-ready and maintainable
• Mentor Rising Talent: Guide junior analytics engineers and data scientists, sharing your expertise in pipeline design, SQL optimisation, and Python development. You'll help build the next generation of analytics engineering talent at QuantSpark
• Shape Client Solutions: Work directly with clients to understand their business challenges and translate requirements into technical solutions
• Innovate with Purpose: Explore cutting-edge approaches to analytics engineering, from modern data stack implementations to MLOps practices, ensuring QuantSpark stays at the forefront of the industry
• What Success Looks Like in Your First Year
• Technical Impact: Successfully lead 3-4 major analytics engineering projects, delivering robust data pipelines that drive measurable business outcomes for clients
• Quality Leadership: Establish data quality frameworks and testing practices that become standard across our analytics teams
• Team Development: Mentor 1-2 junior team members, helping them advance their technical skills and project ownership capabilities
• Client Relationships: Build strong relationships with key technical stakeholders at major clients, becoming a trusted advisor for their data strategy
• Innovation Contribution: Introduce new tools, practices, or methodologies that improve our team's efficiency and solution quality
• We believe in transparency about the realities of joining a scale-up consultancy:
• Complex, Messy Data: Real client data is rarely clean or well-structured. You'll need creativity and technical skill to build robust pipelines that handle edge cases, missing data, and evolving schemas while maintaining data quality
• Diverse Technical Stacks: Each client brings different tools and constraints. You'll work across various cloud platforms, databases, and analytics tools, requiring adaptability and continuous learning
• Balancing Speed and Quality: Clients need results quickly, but our reputation depends on delivering robust, scalable solutions. You'll help teams maintain engineering excellence under time pressure
• Building While Flying: Unlike established enterprises, we're still developing some of our data engineering standards and practices. You'll help shape these systems while navigating some ambiguity
• Competitive Analytics Market: With data engineering roles growing 20% year-over-year, you'll help us stay competitive by developing cutting-edge capabilities while mentoring talent in high demand
• The right candidate will see these challenges as energising opportunities to create outsized impact in a growing organisation