Senior Staff Data Engineer

BILL

12d•$166,400 - $244,800•Remote

About The Position

The Data Platform team builds and operates BILL’s core data infrastructure, providing the end-to-end foundation that collects, stores, processes, governs, and serves data so every team at BILL can use it. We own the full data stack: inbound and outbound data lake, real-time streaming pipelines, batch processing, and data access layers including a Starburst query engine, Databricks Feature Store, Neo4j Knowledge Graph, and OpenSearch. Some capabilities require real-time access with strict low-latency SLAs. Our charter is to simplify the data landscape and power AI at BILL. To achieve this, we focus on building scalable platform capabilities rather than creating one-off pipelines or analytics reports. Engineers here work at the systems level: designing architectures, incubating new capabilities, setting standards, and enabling the rest of BILL to self-serve. The team sits within the CTO organization.

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.

Nice To Haves

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.

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.