Data Engineer

We have a new opportunity for an experienced Data Engineer to join us on a permanent basis in London. This role is offered with hybrid working (more details shared below).

Joining the Penguin Data Engineering team and working closely with DK, you’ll help to shape and improve how data is accessed, understood and used across both businesses.

You’ll be part of the PRH Data Centre of Excellence, a collaborative team that sets shared standards, provides peer support and helps our business areas get the best from their data.

In this role, you’ll work closely with colleagues across DK and PRH, including Technology, Data and Analytics, Commercial Insights, Finance, Operations and Production, Online Marketplace, and Sales teams.

As Data Engineer, you’ll design, build and maintain reliable, secure and reusable data pipelines, models and automation for DK. You’ll help to make trusted data available for reporting, analytics and operational workflows, essentially making it easier for DK teams to access, understand and use data confidently.

Reporting to the Head of Data Engineering, you’ll work with tools and platforms such as Snowflake, Python, SQL, dbt, Fivetran, Power BI, Microsoft Fabric, Git Hub and cloud services. You’ll also support strong data governance, documentation, monitoring and service quality. This role would suit someone who enjoys solving practical data problems, working with both technical and non-technical colleagues, and building solutions that are robust, scalable and genuinely useful.

• Build and manage data pipelines so that data can move reliably between systems and be used for reporting, analytics and day to day operations.
• Maintain DK’s Snowflake data environment, including data models, schemas, performance, and data quality controls.
• Bring together data from different internal and external sources and make sure it is secure, accessible and aligned with PRH data standards.
• Automate manual data and reporting processes using cloud tools, Git Hub and other services to improve efficiency and reliability.
• Manage CI/CD processes for data solutions, making sure development is properly tested, documented and moved between environments safely.
• Support BI and reporting needs, working with analysts and stakeholders on dashboards, reports and tools such as Power BI and Microsoft Fabric.
• Create clear documentation including technical notes, data definitions and service transition materials.
• Support testing, incident resolution and performance monitoring for DK data solutions.
• Lead technical conversations and reviews, sharing best practice across data engineering, automation, data modelling and BI.
• Keep improving DK’s data infrastructure by staying current with tools and identifying better ways of working.
• Work closely with Data Governance, making sure monitoring, alerting and metadata are kept up to date,

• Strong experience in data engineering, business intelligence development or data platform engineering, with a proven track record of designing, building and supporting scalable data integration solutions.
• Strong knowledge of Snowflake and other cloud data platforms, including schema design, data modelling, secure access and performance management.
• Excellent SQL skills, ideally within Snowflake, including data extraction, transformation, analysis, performance optimisation and working with large, structured datasets.
• Strong Python skills for data processing, automation and integration, with the ability to build maintainable, well documented solutions.
• Practical experience of building and managing data pipelines using ETL or ELT frameworks, with knowledge of tools such as dbt, Fivetran or similar.
• Understanding of BI data modelling and reporting tools, such as Power BI, Microsoft Fabric or Looker, including how to structure data for reporting and self-service analytics.
• Experience working with technical and non-technical stakeholders to understand requirements, translate business needs into data solutions, and support the accurate use of data across an organisation.
• A good understanding of data governance, data quality, privacy and compliance…