Senior Manager, Data Platform - T0

This team designs intelligent, autonomous systems that eliminate financial operations for companies globally. We automate everything from bookkeeping and reconciliation to tax, payroll, forecasting, and document understanding: turning hours of work into seconds. As a Senior Manager of Data Platform Engineering, you'll lead the team responsible for the data backbone of our financial systems. You'll set the technical direction for high-volume financial data ingestion, our Databricks lakehouse, data orchestration, canonical financial models, and the infrastructure that makes our data platform reliable, scalable, and increasingly real-time. You'll combine strong technical judgment with people leadership, building a high-performing engineering organization, establishing platform standards, driving major migrations, and partnering closely with product, accounting, and platform teams. This role is based in San Francisco.

Responsibilities

Lead and grow a high-performing data platform engineering team, providing technical direction, mentorship, career development, and clear ownership; Set the technical strategy for high-volume financial data ingestion across payment processors, banks, billing systems, and ERP/GL platforms, with strong guarantees around correctness, replayability, and recovery; Lead the evolution of the Databricks lakehouse using Spark, Delta Lake, Unity Catalog, dbt, Python, and SQL, optimizing for scale, performance, reliability, and cost; Define standards for data contracts, schema evolution, drift detection, data quality, and canonical financial models; Evolve the platform from batch toward near-real-time processing using Kafka, CDC, micro-batching, incremental processing, and Dagster orchestration; Own the architecture of canonical financial models that transform complex source data into consistent financial objects and relationships powering the accounting engine; Partner with infrastructure and platform teams to build reliable production foundations across observability, alerting, incident response, recovery, and operational readiness; Guide infrastructure strategy across GCP, Terraform, Kubernetes/GKE, Helm, GitOps, and CI/CD; Lead migrations from legacy pipelines to the lakehouse, with rigorous parity validation, staged rollouts, and clear rollback strategies; Drive performance and cost optimization across PostgreSQL, Databricks, and large-scale data workloads; Partner with product, accounting, ML, and platform leadership to translate business needs into scalable data platform capabilities; Set technical direction through architecture reviews, design documents, engineering standards, and long-term platform roadmaps; Champion AI-assisted engineering practices that improve team velocity while maintaining high standards for code quality, testing, security, and reliability

Requirements

8+ years of experience in data platform, backend, or infrastructure engineering, including significant experience leading engineering teams; Proven experience managing and developing senior engineers and technical leads and building strong, autonomous teams; Deep expertise in data platforms, distributed systems, data modeling, and production data pipelines; Strong experience with Python and SQL, plus hands-on experience with Spark, Databricks, Delta Lake, dbt, and modern lakehouse architectures; Experience building reliable ingestion systems with large-scale backfills, incremental processing, checkpointing, rate-limit handling, idempotency, and failure recovery; Strong understanding of streaming and event-driven architectures, including Kafka, CDC, and micro-batching; Experience with data orchestration platforms such as Dagster and designing for freshness, partitioning, and incremental computation; Experience optimizing PostgreSQL and analytical workloads for performance and cost; Experience operating production infrastructure on GCP, with familiarity with Terraform, Kubernetes/GKE, Helm, GitOps, and CI/CD; Strong understanding of observability, reliability engineering, and production operations; Excellent technical communication skills, with the ability to influence architecture and engineering decisions across teams; Experience leading complex technical migrations and balancing long-term platform strategy with near-term business priorities; Passion for building teams and infrastructure that power reliable, scalable, mission-critical financial systems