EMNET
Senior Data Engineer
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Senior Data Engineer
Location: UK/EU (Remote)
Employment Type: Full-time
Company: EMNET (on behalf of a client)
Package: Salary + Bonus + Benefits + Stock Options (ISO)
Are you looking to build scalable data platforms that power the next generation of FinTech and AI-enabled products? EMNET is partnering with a high-growth, Series B-funded AI FinTech to hire an experienced Senior Data Engineer as the business continues to scale its technology, data and AI capabilities.
You will play a key role in designing and developing the data infrastructure behind critical financial products, analytics and AI-enabled functionality. This includes building reliable data pipelines, improving how complex datasets are structured and accessed, and creating the foundations that allow Engineering, Product and AI teams to build effectively at scale. This is a senior engineering position with significant ownership across data architecture, pipelines, infrastructure and technical decision-making.
The business offers a highly competitive salary alongside bonus, benefits and stock options (ISO). The role is remote, with a preference for UK-based candidates, although strong candidates across the EU will also be considered.
The Role
- Design, build and maintain scalable data pipelines and infrastructure
- Develop reliable systems for ingesting, transforming and processing large and complex datasets
- Contribute to data architecture and platform design decisions
- Build and optimise data models supporting product, analytics and AI/ML use cases
- Develop data infrastructure capable of supporting AI-enabled and data-intensive products
- Work closely with Engineering, Product and AI teams to make high-quality data accessible across the platform
- Improve data quality, reliability, lineage, observability and performance
- Support the development of scalable cloud-based data infrastructure
- Take ownership of complex technical challenges from initial design through to production
- Contribute to engineering standards, tooling and best practices across the data function
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Requirements
- Significant commercial experience as a Data Engineer or in a closely related data engineering role
- Strong proficiency in Python and SQL
- Experience designing and building production-grade data pipelines
- Strong understanding of data modelling, ETL/ELT and modern data architecture
- Experience working with AWS, GCP or Azure
- Experience with modern data warehouses, lakehouses or distributed data platforms
- Strong understanding of data quality, reliability and performance
- Experience working with large, complex or high-volume datasets
- Strong communication and stakeholder management skills
- Ability to operate independently and take ownership of technical initiatives
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Desirable
- Experience within FinTech, WealthTech or financial technology
- Experience working with financial, investment or transactional datasets
- Exposure to AI/ML platforms, LLM applications or data infrastructure supporting machine-learning systems
- Understanding of data requirements for training, evaluation or production AI workloads
- Experience with technologies such as Snowflake, Databricks, dbt, Airflow or Spark
- Experience with vector databases, embeddings or retrieval-based AI systems
- Experience with Docker, Kubernetes and CI/CD environments
- Experience within a high-growth or startup environment
- Previous experience mentoring or supporting other engineers
Additional Information
We're interested in speaking with experienced Data Engineers who enjoy solving complex data problems and building infrastructure that can scale alongside rapidly evolving products. You don't necessarily need to meet every requirement. Strong engineers who can demonstrate significant experience building reliable, production-grade data systems are encouraged to apply. If you're looking for an opportunity to work across data engineering, FinTech and emerging AI capabilities within a high-performing engineering environment, we'd love to hear from you.
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