Staff Data Engineer

Role overview

Join Payabli as the founding Staff Data Engineer for the Data Engineering team. You’ll make foundational architecture decisions for the company’s payments data platform, build and operate pipelines, and define canonical datasets and models that power analytics and AI/ML.

Key missions

• Architect the data platform and set the direction for the warehouse/lakehouse, including the data lake and layered architecture.
• Design and run batch + streaming pipelines moving data reliably from production systems with data quality and observability.
• Define canonical datasets and models used across the company, ensuring correctness and regulatory compliance.

Responsibilities

• Own end-to-end data engineering decisions from design through production.
• Ensure reliability, accuracy, and compliance for regulated payments data.
• Enable downstream use cases for analytics and AI/ML.

Requirements

• 8+ years building production data systems, with a track record of owning architecture and delivering major decisions to production.
• Strong pipeline orchestration experience (e.g., Airflow, Dagster, Prefect, or equivalent) and large-scale processing (e.g., Spark).
• Expert SQL and strong Python.
• Strong data modeling skills (dimensional/normalized/Data Vault) and ability to design models that “age well.”
• Deep experience with a modern lakehouse/warehouse ecosystem (e.g., Snowflake + dbt + Fivetran or Databricks + Spark + Delta Lake + Unity Catalog).
• Experience with sensitive/regulated data, including access controls, encryption, governance, and risk management.
• Production cloud experience on AWS, GCP, or Azure, including security and cost patterns.

Nice-to-haves / additional focus areas

• Payments/fintech or other regulated-domain experience, including familiarity with PCI DSS and tokenization/vaulting patterns.
• Streaming infrastructure experience (Kafka, Kinesis, Flink).
• Data governance, lineage, and observability tooling (e.g., Unity Catalog, Snowflake Horizon, Monte Carlo, Great Expectations, OpenLineage).
• Interest in growing into people leadership as the function scales.
• Experience supporting ML/AI workloads (feature stores, training/inference pipelines, MLflow).