Data Engineer - Gibraltar

Entain
Málaga, Spain
13 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours

Tech stack

Airflow Amazon Web Services Data Analysis Microsoft Azure BigQuery Cloud Computing Cloud Engineering Continuous Integration Data Governance Data Transformation Data Systems Distributed Computing Environment
+18 more
Github Python (Programming Language) Azure Data Lake SQL Databases Azure Data Factory Snowflake Grafana Gitlab Event Driven Architecture Infrastructure Automation Frameworks Data Analytics Data Management Terraform Azure Synapse Analytics Software Version Control Data Pipelines Docker Databricks

Job description

OverviewAs 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 / Beneficiosregular bonuspension25 days annual leavewellbeing and development dayslife assuranceIncome Protection cancellation?(unknown context, keep as listed)ResponsabilidadesDesign, build and maintain scalable data pipelines turning diverse data into business-ready productsEnhance data quality frameworks with monitoring and validation to ensure trusted dataPartner with business, marketing and tech teams to translate requirements into solutionsContribute to solution architecture and manage delivery from discovery to implementationCollaborate with central data, platform and engineering teams to align with enterprise standardsDrive continuous improvement across processes, datasets and tools to increase valueConvey technical concepts clearly to both technical and non-technical stakeholdersChampion engineering best practices in testing, observability, documentation and maintainabilityEvaluate new data sources, technologies and approaches to expand analytics capabilitiesThrive in a fast-paced environment defining requirements and delivering pragmatic solutionsRequisitos principalesStrong experience building and maintaining data pipelines using SQL, Python, or similarExperience 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 platformsExperience 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 practicesclear communication with both technical and non-technical stakeholderscollaboration across cross-functional teamsability to prioritise and adapt in a fast-paced environmentSQLPythonSnowflake

Requirements

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

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