Senior Data Engineer

A high-growth fintech business is looking for a Senior Data Engineer to join their Data Science and Engineering team. You will play a key role in designing and delivering scalable, production-ready analytical solutions that turn complex transactional data into meaningful insights.

You will own and improve the systems that ingest, transform and serve large-scale datasets, working closely with data science and product teams to produce measurable engineering outcomes.

Responsibilities

• Design, build and operate data ingestion and ETL/ELT pipelines powering analytics and customer-facing applications
• Build and maintain data platform architecture including pipelines, warehouses and reporting infrastructure
• Implement data modelling, schema design and data contracts to make datasets easy to consume
• Introduce and maintain observability, data quality checks and automated testing for production data flows
• Collaborate with product managers and cross-functional teams to translate customer needs into data-driven solutions
• Optimise performance and cost of data processing and storage across cloud services
• Communicate technical findings clearly to both technical and non-technical stakeholders

Do you have experience in SQL?, Do you have a Bachelor's degree?, * Bachelor's degree in Computer Science, Data/Software Engineering or related discipline

• 5+ years hands-on data engineering experience delivering scalable, production-grade platforms
• Strong SQL skills and proven experience designing and optimising data pipelines and warehouse schemas
• Strong Python proficiency for production data engineering
• Track record implementing data quality, observability and testing practices
• Solid experience with at least one cloud provider (Azure, AWS or GCP)
• Experience with CI/CD, infrastructure-as-code and containerised environments
• Familiarity with modern data stack tools such as Databricks, Snowflake or Redshift
• Experience with reporting tools such as Power BI

Bonus

• Experience in large-scale regulated data environments
• DevOps for data, platform engineering or real-time data streaming
• Background in high-growth, product-led environments