About the Role
This is a hybrid role. As a Data Engineer, you will be responsible for designing and building scalable, resilient data solutions that power analytics, marketing effectiveness measurement, and decision-making across Entain's industry-leading digital brands. You'll work at the heart of our data ecosystem, creating the platforms and datasets that enable teams to generate insights, optimise performance, and drive commercial growth.
Responsibilities
•Design, build and maintain scalable data pipelines, transforming complex internal and external data into reliable, business-ready data products.
•Develop and enhance data quality frameworks, monitoring and validation processes to ensure accurate, timely and trusted data.
•Partner with business, marketing and technology teams to translate requirements into effective data solutions and challenge assumptions where needed.
•Contribute to solution architecture and technical design, owning delivery from discovery through to implementation and ongoing support.
•Collaborate with central data, platform and engineering teams to ensure alignment with enterprise standards and strategic objectives.
•Drive continuous improvement across processes, datasets and tools, increasing efficiency, reliability and business value.
•Communicate technical concepts and recommendations clearly to both technical and non-technical stakeholders, including senior leaders.
•Champion engineering best practices in testing, observability, documentation and maintainability to deliver scalable, resilient solutions.
•Evaluate new data sources, technologies and approaches to expand analytical capabilities and shape the future data landscape.
•Thrive in a fast-paced environment, helping define requirements and deliver pragmatic solutions where processes and ownership models are evolving.
Requirements
•Strong experience building and maintaining data pipelines using SQL, Python, or similar technologies.
•Experience with modern cloud data platforms, ideally Snowflake, or alternatives such as Databricks, Redshift, Synapse, BigQuery, or Azure Data Lake.
•Experience developing cloud-based solutions, with AWS preferred, or equivalent experience in Azure or GCP.
•Familiarity with data transformation and ELT frameworks, ideally dbt.
•Experience implementing data quality, testing, monitoring, and observability solutions, with tools such as Monte Carlo.
•Experience with workflow orchestration tools, preferably Prefect, or alternatives such as Airflow, Dagster, or Azure Data Factory.
•Understanding of event-driven architectures, distributed data processing, and large-scale data platforms.
•Experience with source control and CI/CD practices, ideally using GitLab, GitHub, or Azure DevOps.
•Familiarity with containerisation technologies such as Docker or Podman, and Infrastructure-as-Code tools such as Terraform.
•Strong understanding of data modelling, warehousing, and analytics engineering best practices.
•Excellent stakeholder management and communication skills, with the ability to translate business requirements into scalable technical solutions.
Benefits
•A regular bonus and great pension.
•25 days annual leave and all Bankholidays.
•Extra paid leave, including wellbeing and development days.
•Life assurance and Income Protection.
•Private healthcare and wellbeing support.
•A stake in our success through our ShareSave scheme.
