Senior Data & ML Engineer

About the role

Paysend is looking for a highly autonomous Senior Data & ML Engineer who owns data end-to-end, from scoping and design through delivery, implementation and business adoption. The role works directly with commercial stakeholders (Product, Finance, Operations, Compliance and Marketing) and engineering teams, and leads machine learning engineering by moving predictive models into production with infrastructure, automated MLOps pipelines and serving architectures.

Key responsibilities

• Design, build and maintain data pipelines and transformations on Databricks using Python, PySpark and SQL.
• Deploy, operationalise and monitor machine learning models in production (MLOps).
• Build and maintain data marts and apply data modelling practices such as dimensional modelling and medallion architecture.
• Implement data quality checks, monitoring and alerting, and optimise pipeline performance and cost.
• Lead engineering standards and process improvements across the data team.
• Act as the primary data partner for business areas, translating requirements into technical solutions and managing trade-offs.
• Build and maintain datasets for reporting and dashboards in Preset, onboard users and promote data definitions, documentation and governance.

Required profile

• 5+ years as a Data/ML Engineer, owning solutions from scoping to adoption.
• Stakeholder management and clear, structured communication in English.
• Nice to have: fintech or payments experience, experience with sensitive data (GDPR), mentoring experience, and interest in AI tools for data engineering.

Required skills

• Python, SQL and PySpark/Spark.
• Databricks (Delta Lake, Unity Catalog, MLflow, workflows).
• Data modelling and data marts for analytics and reporting.
• Production pipelines with orchestration, testing, monitoring and version control.
• BI tools such as Preset, Tableau, Metabase or Power BI.
• Nice to have: ML engineering, Terraform/Tofu, AWS/Azure/GCP, CI/CD, and infrastructure as code.