Paysend

Data Engineer

• Design, build, and maintain data pipelines and transformations on Databricks using Python, PySpark, and SQL
• Deploy, operationalize, and monitor machine learning models in production environments
• Build and maintain data marts as the primary source of truth for key business domains
• Apply data modelling practices such as dimensional modelling and medallion architecture
• Implement data quality checks, monitoring, and alerting
• Optimize pipeline performance and cost-efficiency
• Lead and contribute to engineering standards and process improvements across the data team
• Act as the primary data partner for assigned business areas
• Manage end-to-end solutions from scoping and discovery through design, delivery, user adoption, and iteration
• Gather and translate business requirements into technical solutions
• Communicate with engineering peers and commercial stakeholders to define priorities and manage trade-offs
• Identify opportunities where data or machine learning can improve decisions, efficiency, or customer outcomes
• Build and maintain datasets powering reporting and dashboards in Preset
• Onboard and support users on Preset
• Promote data definitions, documentation, governance, and self-service data practices

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Senior Data Engineer