# Director of Data Platform

**Company:** [Alpaca](https://hotfix.jobs/companies/alpaca)
**Location:** Remote
**Role:** Data Engineering
**Experience:** 8+ years
**Skills:** Python, SQL, dbt, Trino, Apache Iceberg, GCP, Airflow, Kubernetes, Terraform, Kafka, Reverse Etl, BigQuery, Helm, Gcs, GKE
**Posted:** 2026-08-12

> 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.

## Job Description

## 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.

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