Make your impact within a rapidly growing Fintech Company

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.

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.

We’d love to chat if you have:

• 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.

Desired Qualifications:

• 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.