Design, build and maintain scalable data pipelines and backend services
Support real-time decisioning, analytics, reporting and data collection
Translate business/data requirements into appropriate data models and technical solutions
Manage data transformation, integration and processing
Develop high-quality, secure and well-tested code
Build solutions that improve data governance, security and quality
Implement processes and controls around Data Security and Data Quality
Collaborate with developers and stakeholders while providing technical guidance

5+ years' Data Engineering experience, particularly ETL/ELT, Data Warehousing and BI
5+ years building end-to-end data systems/pipelines using Python and/or Scala
Strong SQL skills, including data analysis, troubleshooting and root-cause analysis
Hands-on experience with Databricks, PySpark, Spark Streaming and Delta Lake
Experience with large-scale datasets and complex data transformations
Strong experience with cloud-based data platforms, ideally Microsoft Azure
Experience with Azure Data Lake / Blob Storage or comparable cloud storage
Good understanding of data modelling and data architecture principles
Experience working within CI/CD environments
Exposure to event-driven architectures such as Kafka, Event Hubs or Apache Flink
Experience with Docker / Kubernetes / Helm and containerised environments
Knowledge of dbt and BI/reporting tools
Strong communication skills with the ability to provide technical guidance/leadership

Senior Data Engineer – Data Analytics Platform

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