Overview
Todas las habilidades, cualificaciones y experiencia relevantes que necesitará un candidato seleccionado se enumeran en la siguiente descripción.
As a Data Engineer at Entain, you design and build scalable data pipelines and platforms that power analytics, marketing effectiveness, and decision-making across our digital brands. You will join the Group Analytics Data Engineering Team, delivering robust data solutions that enable insights, optimised campaigns, and commercial growth. Your work directly supports budget allocation, performance improvements, and regulatory reporting at scale. You will operate in a fast-paced, cross-functional environment where data quality, observability, and collaboration matter to impact the business.
Compensaciones / Ventajas
regular bonus
pension
25 days annual leave
wellbeing and development days
life assurance
Income Protection cancellation? (unknown context, keep as listed)
Responsabilidades
Design, build and maintain scalable data pipelines turning diverse data into business-ready products
Enhance data quality frameworks with monitoring and validation to ensure trusted data
Partner with business, marketing and tech teams to translate requirements into solutions
Contribute to solution architecture and manage delivery from discovery to implementation
Collaborate with central data, platform and engineering teams to align with enterprise standards
Drive continuous improvement across processes, datasets and tools to increase value




Convey technical concepts clearly to both technical and non-technical stakeholders
Champion engineering best practices in testing, observability, documentation and maintainability
Evaluate new data sources, technologies and approaches to expand analytics capabilities
Thrive in a fast-paced environment defining requirements and delivering pragmatic solutions
Requisitos principales
Strong experience building and maintaining data pipelines using SQL, Python, or similar
Experience with modern cloud data platforms (Snowflake, or Databricks, Redshift, Synapse, BigQuery, Azure Data Lake)
Experience developing cloud-based solutions (AWS preferred or Azure/GCP equivalent)
Familiarity with data transformation and ELT frameworks (dbt)
Experience implementing data quality, xhfqzwm testing, monitoring, observability tools (e.G., Monte Carlo)
Experience with workflow orchestration tools (Prefect preferred;
Airflow, Dagster, AzureData Factory as alternatives)
Understanding of event-driven architectures, distributed data processing, and large-scale platforms
Experience with source control and CI/CD (GitLab, GitHub, or Azure DevOps)
Familiarity with containers (Docker or Podman) and IaC tools (Terraform)
Strong data modelling, warehousing and analytics engineering practices
clear communication with both technical and non-technical stakeholders
collaboration across cross-functional teams
ability to prioritise and adapt in a fast-paced environment
SQL
Python
Snowflake

📌 Data Engineer (Valencia)
🏢 Entain
📍 Valencia