Graduate Data Engineer in Edinburgh

Your role As a Senior Data Engineer with Atto, you will be part of our Data Science & Engineering team, helping our customers use transactional intelligence to drive smarter financial decisions and build impactful products. You’ll play a key role in designing and delivering scalable, production-ready analytical solutions that turn complex data into meaningful insights.

You will own and improve the systems that ingest, transform, and serve large-scale transactional data sets. You will be responsible for designing resilient data pipelines, implementing robust data models, deploying real-time and batch processing systems, and introducing observability, testing and automation to keep our data trustworthy at scale. You will work closely with the data science and product teams to understand customer needs and the direction of internal strategy, producing measurable data engineering outcomes.

We’re looking for someone who’s passionate about technology, curious about data infrastructure, and excited to solve real problems. You’ll need a strong foundation in data engineering, a creative mindset, and the ability to communicate clearly with both technical and non-technical stakeholders. You’ll be supported with training and development opportunities to deepen your expertise and stay ahead of industry trends.

Responsibilities

• Design, build, and operate data ingestion and ETL/ELT pipelines for our data systems that power Atto products and customer-facing applications.
• Build and maintain our data platform architecture and infrastructure, including data pipelines, warehouses that power analytics and product features and reporting.
• 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 our production data flows.
• Driving impact at scale by improving data workflows, service reliability, and making Atto’s capabilities faster, more reliable and widely accessible.
• Collaborate with product managers and cross-functional teams to translate market signals and customers’ needs into innovative data-driven solutions.
• Create new systems and approaches, while continuously improving and scaling existing ones for performance, reliability, and efficiency.
• Conduct deep analysis of transactional datasets to validate data models, surface data quality issues, and propose engineering fixes.
• Optimise performance and cost of data processing and storage across cloud services.
• Communicate technical findings and recommendations clearly to both technical and non-technical stakeholders across the business.
• Stay current with industry developments, emerging technologies, and best practices in data engineering.

Requirements

• A Bachelor's degree in Computer Science, Data/Software Engineering, or a related discipline.
• 5+ years of hands-on experience in data engineering with a proven track record of delivering scalable, production-grade data platforms and data models.
• Strong SQL skills and proven experience designing, building and optimising data pipelines and data warehouse schemas.
• Strong proficiency in Python for production data engineering with a focus on building maintainable, testable and clean code.
• Track record of implementing data quality, observability, monitoring and testing practices.
• Solid experience with at least one cloud provider (Azure, AWS or GCP), and their managed data services.
• Experience with CI/CD, infrastructure-as-code and working in containerised environments.
• Familiarity with modern data stack tools: Databricks, Snowflake or RedShift, etc.
• Experience working with reporting and modelling tools such as Power BI, including designing performant data models and supporting self-serve analytics.
• Advanced experience in pattern recognition with the ability to translate complex data into actionable insights.
• A results-oriented mindset, able to take concepts from ideation through to tangible outputs.
• Comfortable working in a fast-paced, delivery-focused environment, balancing multiple priorities with agility.
• A proactive and collaborative approach, with a willingness to iterate, share knowledge, and challenge assumptions constructively.

Bonus Points

• Experience building or scaling data platforms in large-scale, regulated data environments.
• Experience with DevOps for data, platform engineering, or building large data pipelines and real-time data streaming systems.
• Exposure to working in a high-growth, evolving environment where the customer is at the heart of product and engineering decisions.