Senior Staff Data Engineer

BILL is a fintech company that provides financial automation tools for businesses. The Senior Staff Data Engineer will architect and operate scalable data platform infrastructure across ingestion, storage, processing, governance, querying, and serving, while establishing technical standards and enabling self-service data capabilities. The role also involves leading enterprise-scale migrations, partnering across engineering teams, and mentoring senior and staff engineers.

Responsibilities:

• Operate at the architectural level, driving platform-wide technical decisions and mentoring the team
• Own and evolve critical infrastructure across the full data lifecycle, spanning ingest, store, enrich, query, and serve
• Architect and own critical data platform capabilities end-to-end, from inbound ingestion through data lake storage to downstream serving, including the feature store, query engine, knowledge graph, and search
• Define technical direction for the team’s most complex, cross-cutting problems, such as streaming versus batch trade-offs, schema contracts, data access patterns, and real-time serving architectures
• Drive design and delivery of new capabilities from inception to GA, including reference implementations, SLAs, and clear ownership handoff models
• Establish and maintain architectural standards and engineering patterns adopted across the organization
• Lead multi-phase technical migrations at enterprise scale, including compute platform upgrades, warehouse-to-lake migrations, and infrastructure modernization
• Partner with engineering teams across BILL, such as ML/AI, Risk, Payments, and Analytics, to translate diverse data needs into durable platform solutions
• Mentor senior and staff engineers, actively shaping the technical culture and engineering quality bar of the team
• Own and continuously improve critical production systems with a focus on reliability, cost efficiency, and a self-serve developer experience

Requirements:

• Bachelors degree in Computer Science, Engineering, Mathematics, or equivalent work experience
• 8+ years of experience in data engineering, distributed systems, or software engineering with a heavy focus on data infrastructure
• 5+ years of experience specifically on data platform, data infrastructure, or data systems teams, rather than purely analytics or BI roles
• Expertise in distributed systems design for data workloads, including a deep understanding of streaming, batch, and real-time serving trade-offs
• Hands-on experience with event streaming platforms (such as Kafka, Flink, Spark Streaming, or equivalent) and CDC-based ingestion patterns
• Strong proficiency with batch processing stacks (such as Airflow, dbt, Spark/Glue, or equivalent)
• Experience with modern open table formats and data lake architectures, including Apache Iceberg, Delta Lake, or equivalent frameworks
• Familiarity with data access and serving layers, including query engines (Trino/Starburst, Presto), feature stores, vector stores, or graph databases
• Expert-level SQL and strong Python skills, backed by solid software engineering fundamentals such as CI/CD, testing, and observability
• Demonstrated experience architecting and operating large-scale, production-grade data platforms
• A proven track record operating as a technical lead, with the ability to drive ambiguous, high-impact projects from first principles to production
• The ability to define technical standards that hold across organizational boundaries rather than just within a single team
• 3+ years of experience in financial services, fintech, or SaaS companies
• Experience building self-serve data platforms or developer-facing infrastructure tooling
• Experience working in fintech, financial data, or highly regulated data environments