Data Engineer

Autopay Global is the newest member of the Autopay family, aiming to expand the reach of the group’s state-of-the-art payment integration and payment data technologies to the international market, providing seamless integration with local PSPs, support for multiple currencies and compliance with local frameworks.

• 5+ years in data engineering with production pipeline ownership; strong software engineering discipline
• Hands-on proficiency with PySpark and Spark performance tuning (shuffle optimization, partitioning, checkpointing, incremental loads)
• Experience with Databricks (jobs/workflows, Delta Lake, governance) or equivalent lakehouse platforms
• Experience building both streaming and batch pipelines that power real-time product features (not only analytics/BI)
• Understanding of data modeling (star schema, SCD, Bronze/Silver/Gold) and schema evolution strategies
• Experience with at least one CDC tool (Datastream, Debezium, DMS) and event streaming (Kafka or Pub/Sub)
• Familiarity with data governance concepts: lineage, data contracts, PII handling, and consent enforcement
• Growth mindset and ability to apply new technologies, patterns or solutions to the current workstream (i.e. GenAI-assisted coding)
• Communication and interpersonal skills

• Build and maintain PySpark pipelines in Databricks for streaming and batch workloads
• Implement and manage data ingestion from diverse sources using APIs, change data capture, event streaming, and webhooks
• Design and enforce the Bronze/Silver/Gold lakehouse layers on GCS with Delta Lake
• Build and maintain Customer 360 / CDP datasets
• Develop and operate feature store pipelines
• Implement schema evolution with schema registry, data contracts, and automated compatibility checks across streaming and batch ingestion
• Own pipeline observability: set up monitoring for freshness, completeness, schema drift, and anomaly detection
• Collaborate with AI Engineers on embedding and feature data pipelines
• Contribute to data governance: lineage tracking, PII tagging, access reviews, and quality SLA enforcement
• Participate in on-call rotations and incident response for production data systems