Director of Data Platform
Leads Alpaca’s data department across platform engineering, analytics engineering, and data science, owning strategy, architecture, execution, and operational reliability. The role requires extensive data engineering and people-management experience, modern data-stack expertise, and familiarity with financial services data.
About the job
Responsibilities
- Lead and develop three sub-teams: Platform Engineering & ETL, Analytics Engineering, and Data Science & Analytics.
- Manage team leads, set priorities, and ensure delivery.
- Own the data lakehouse architecture, including Trino, Iceberg/GCS, Airflow, Airbyte, Redpanda CDC, and dbt; make build-vs-buy tooling decisions.
- Drive partner invoicing accuracy and evolution by ensuring invoicing logic is versioned, reproducible, and scalable.
- Deliver embedded analytics through BrokerDash, SSR pipelines, and API-based reporting; own row-level security and entitlements.
- Support product launches through data change management across downstream datasets, dashboards, and reverse ETL.
- Accelerate self-service analytics through semantic layers, data catalogues, and conversational BI.
- Guide enterprise AI search, agent-based workflow automation, and LLM-powered analytics.
- Collaborate with Finance, Sales, Product, Compliance, and Customer Success to translate business needs into data products.
- Manage infrastructure costs and maintain the data-to-cloud cost ratio under target as assets under custody grow.
- Own on-call processes, incident response, and SLOs for data freshness, accuracy, and availability.
Requirements
- 8+ years of experience in data engineering or analytics, including 3+ years managing data teams.
- Deep experience with modern data stacks, including dbt, Trino/Presto or equivalent query engines, Apache Iceberg or similar table formats, and cloud object storage.
- Hands-on experience with ETL/ELT at scale, including CDC, Debezium/Kafka, batch processing, Airflow, dbt, streaming, and reverse ETL.
- Experience building self-service analytics capabilities for non-technical stakeholders.
- Experience with financial data, such as trading, invoicing, revenue attribution, or regulatory reporting, in fintech or financial services.
- Proficiency in Python and SQL, with the ability to read code, review pull requests, and make architecture decisions.
- Experience managing distributed or remote teams across multiple time zones.
- Strong stakeholder-management and communication skills.
- Experience with GCP, including GKE, GCS, and BigQuery migration; Kubernetes; Helm; and Terraform.
Nice-to-Haves
- Brokerage or broker-dealer operations experience, including clearing, settlement, market making, or reconciliation.
- Familiarity with LLM and AI tooling, including MCP, vector databases, enterprise search, and conversational BI tools such as WrenAI and Cube.
- Compliance analytics experience with AML/Actimize, KYC, or margin calls.
- Exposure to open-source data catalogues such as OpenMetadata and Collate, and data quality frameworks.
Compensation & Benefits
- Competitive salary and stock options.
- Health benefits.
- One-time USD $500 new-hire home-office setup.
- USD $150 monthly stipend via a Brex Card.
Skills
Python, SQL, dbt, Trino, Apache Iceberg, GCP, Airflow, Kubernetes, Terraform, Kafka, Reverse Etl, BigQuery, Helm, Gcs, GKE
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