About Us

We’re building the data foundation for the future of commerce and finance. Our platform helps merchants access real-time insights, manage financial risk, and optimize revenue using cutting-edge data infrastructure.

About the Role

As a Staff Data Engineer, you’ll architect and scale our data infrastructure to support mission-critical financial and commerce use cases. You’ll enable robust analytics, operational workflows, and ML integrations that power smarter products and decisions.

What You’ll Do

Design and build scalable, secure, and high-throughput data pipelines supporting payments, risk, reconciliation, and user behavior tracking.

Implement data models and systems for financial reporting, ledger reconciliation, fraud detection, and business analytics.

Collaborate closely with product, engineering, and data science teams to enable data-powered features and experimentation.

Ensure compliance with financial and regulatory data handling standards (e.g., SOC 2, PCI).

Champion data quality, lineage, and governance across the company.

Optimize real-time and batch data architectures for performance and reliability.

Who You Are

8+ years of experience in data engineering, with deep understanding of distributed systems, data modeling, and ETL/ELT processes.

Expertise in modern data platforms (e.g., Spark, Kafka, Airflow, Snowflake, BigQuery).

Experience working in financial systems or with sensitive payment data.

Strong SQL, Python, and data pipeline development skills.

Familiarity with event-driven architecture and real-time analytics.

Nice to Have

Knowledge of ledger systems, reconciliation logic, or fraud detection pipelines.

Experience supporting ML workflows and data observability platforms.

Background in fintech or commerce analytics at scale.