Analytics / Data Engineer

About the role

Own and scale the core data platform that powers reporting, attribution, product analytics, reconciliation, AI workflows, and company-wide decision-making at PFM. Turn fragmented raw data into reliable, reusable business intelligence layers that enable faster decisions and scalable automation.

Responsibilities

• Objective 1 - Own the data platform foundation
• Reliable, well-modelled, documented warehouse data that powers reporting and AI workflows across the company.
• Tasks: Own BigQuery warehouse architecture and dbt models, Manage Airbyte pipelines and tracking infrastructure, Apply orchestration tools (e.g., Airflow) for recurring workflows, Monitor pipeline reliability and address breakages.
• Objective 2 - Build reliable business data models
• A trusted source of truth across revenue, attribution, product funnels, partner performance, finance, and executive reporting.
• Tasks: Model revenue and commission flows end-to-end, Model product funnels for conversion analysis, Model partner performance for the Revenue Operations team, Build executive reporting layers.
• Objective 3 - Improve data quality and reduce manual work
• Reduced reconciliation discrepancies; reduced manual reporting overhead across Finance, Analytics, and Partners teams.
• Tasks: Implement governance, permissions, monitoring, and alerting, Automate recurring reports and reconciliations, Enable self-service analytics for non-technical stakeholders, Improve documentation and discoverability of warehouse tables.
• Objective 4 - Enable AI workflows and new integrations
• AI/automation initiatives scale on clean data; new sources are integrated without manual stitching.
• Tasks: Integrate QuickBooks, CRM, support, social, and operational systems, Support AI enablement (Claude / internal AI assistants) with structured data, Use AI-assisted coding workflows to speed development, Partner with Engineering on integration architecture.

Requirements

• Must have 3+ years of experience as a Data Engineer or Analytics Engineer
• Strong SQL and warehouse modelling skills (dbt, BigQuery preferred)
• Data pipeline engineering experience (Airbyte, orchestration, monitoring)
• Comfortable with workflow orchestration tools (Airflow or similar)
• Strong data governance, quality, and documentation mindset
• Excellent async written communication - we are remote-first

Nice to have

• AI-assisted coding fluency (e.g., Claude, Cursor, Copilot)
• Prior experience in fintech, prop trading, or SaaS
• Experience integrating QuickBooks, CRM, or operational systems
• Cross-functional partnership experience with Product, Marketing, or Finance

Benefits

• Hiring stages
• Application screening
• Video intro + role fit questionnaire
• Discovery HR Interview
• Real-world task
• Deep-dive Professional interview
• Functional Interview
• Peer & values conversation