Senior Data Engineer
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Senior Data Engineer
London (Hybrid – 2–3 days in office)
The Company
Our client is a fast-growing AI and data analytics scale-up building advanced platforms that help large enterprises better understand customer behaviour and intent. Recognised among the FT1000 fastest-growing companies in Europe, the business is backed by strong investors and serves a global client base across telecommunications, financial services, retail and digital platforms.
Their technology processes billions of interaction events and behavioural signals daily, transforming complex raw data into actionable insights that drive measurable commercial outcomes for enterprise customers.
The company operates internationally with teams across London, Europe and the US, and is continuing to expand its data platform and engineering capabilities as the business scales.
The Opportunity
The company is hiring a Senior Data Engineer to help build and scale the data platforms that power its AI and analytics products.
You will play a key role in designing and operating high-performance data pipelines and distributed systems that transform large-scale behavioural data into reliable intelligence used across multiple products and teams.
This role sits at the intersection of data engineering, platform architecture and analytics, working closely with product, engineering and data science teams.
Key Responsibilities
- Design, build and scale high-performance data pipelines processing millions of customer data events
- Architect cloud-native data platforms focused on reliability, performance and scalability
- Translate analytics and product requirements into production-grade data infrastructure
- Automate data workflows to improve reliability and reduce operational overhead
Candidate Profile
The ideal candidate will have strong experience designing and operating large-scale data platforms in production environments.
Key requirements include:
- Proven experience building data pipelines and distributed data systems at scale
- Strong experience working with cloud platforms (AWS, Azure or GCP)
- Expertise in SQL and at least one backend language (Python, Scala, Java or similar)
- Hands-on experience with data warehousing and ETL / ELT workflows
- Familiarity with modern analytics platforms such as Snowflake, BigQuery or Databricks
- Strong focus on performance optimisation, reliability and automation
- Comfortable working cross-functionally with engineering, analytics and product teams
Working Environment
- Hybrid working model (London office 2–3 days per week)
- Collaborative, engineering-driven culture
- Opportunity to work on large-scale data problems and real-world AI applications
- Fast-growing environment with significant scope for career progression
Benefits
- Private medical insurance
- Life assurance and income protection
- Pension scheme
- Enhanced parental leave
- 26 days holiday (increasing with service)
- Flexible working options
- Training and development opportunities
- Wellbeing programme and mental health support
- Cycle to work scheme
- On-site gym access
- Daily breakfast and weekly lunch in office