Overview

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 / Incentivos

- 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, testing, monitoring, observability tools (e.g., Monte Carlo)
- Experience with workflow orchestration tools (Prefect preferred; Airflow, Dagster, Azure Data 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 (Andalucía)
🏢 Entain
📍 Andalucía