Senior Data Engineer

What you’ll do

• Design and build data pipelines and datasets supporting one or more product areas within an established, governed data platform.
• Implement ingestion patterns for batch, streaming, and event data, onboarding new data sources using existing frameworks and standards.
• Build and maintain reliable data pipelines with appropriate data quality checks, basic lineage, monitoring, and alerting.
• Develop curated datasets and views that are secure, discoverable, and ready for analytics, reporting, and downstream consumption.
• Contribute to customerfacing data products such as datasets, metrics, exports, or feeds, ensuring accuracy and clear documentation.
• Implement data models for both operational databases and analytics stores, following agreed modelling conventions and best practices.
• Support ML and analytics use cases by producing trusted training datasets and featureready outputs with consistent definitions.
• Optimize pipeline performance, cost, and reliability within defined architectural patterns.
• Collaborate with product managers, engineers, analysts, and security partners to deliver data solutions aligned to roadmap needs.
• Participate in oncall rotations and operational support for data services owned by the team.
• Contribute to technical discussions, code reviews, and continuous improvement of data engineering practices.

Required

• Solid experience building and operating production data pipelines and datasets in a cloud environment.
• Strong SQL skills and working Python experience for building data pipelines, transformations, and automation.
• Handson experience with cloud platforms (AWS or Google Cloud), including core services such as compute, storage, IAM, and networking.
• Experience working with both operational databases (e.g., RDSstyle systems) and analytics or columnar data stores.