PFM Global Fzco

Analytics / Data Engineer

United States · Full-time

Sponsorship not specifiedDetected 45 days ago

SQLBigQueryAirflowdbtAI OrchestrationCRMExcelQuickBooksCustomer SuccessCadenceCommunicationProblem SolvingPipeline Integrity

About the role

Prop Firm Match Global FZCO is a leading platform for discovering, comparing, and selecting top proprietary trading firms. We provide traders with tools and features to easily compare challenge details, read verified reviews, see accurate payout data, and much more. We're a fast-moving, fully remote team with members from all around the world caring deeply
about the quality of what we build. Our culture values ownership, clear communication, and practical impact over fluff. Whether you're a trader, technologist, marketer, or operator - your work here shapes how thousands of users find and trust prop firms. About the department Data & Analytics is the function that turns raw business data into decisions. We

Trusted source of truth across revenue, attribution, product funnels, partner performance, finance, and executive reporting.
Model partner performance for the Revenue Operations team.
Build executive reporting layers.
Implement governance, permissions, monitoring, and alerting.
Integrate QuickBooks, CRM, support, social, and operational systems.
Support AI enablement (Claude / internal AI assistants) with structured data.
Partner with Engineering on integration architecture.
This stage is designed to give both sides a realistic view of the work before committing further.

A short async step - no scheduling required.
This helps us understand who you are, your relevant background, and how your experience aligns with the role without either side committing to a live call upfront.
A deep-dive Professional interview You will meet the Head of Data & Analytics at PFM to focus on your technical expertise, analytical methodology, and how you approach real business problems.
What we look for Must have 3+ years of experience as a Data Engineer or Analytics Engineer.

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.
Hiring stages We keep our process simple, transparent, and respectful of your time.
Here's what to expect: 1.
Application screening: We carefully review all applications to identify candidates whose background aligns with the role's requirements.
You'll receive a timely and transparent update on your application status.

Prop Firm Match Global FZCO is a leading platform for discovering, comparing, and selecting top proprietary trading firms.
About the department Data & Analytics is the function that turns raw business data into decisions.
Turn fragmented raw data into reliable, reusable business intelligence layers that enable faster decisions and scalable automation.
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.

We'll explore your analytical thinking, how you communicate insights to different audiences, how you handle ambiguity, and how you operate within cross-functional environments.
Peer & values conversation A conversation with a peer from across the team focused on values, culture, and how you work best.
You'll have plenty of space to ask questions and get a real feel for life at PFM.
If there's a strong mutual match, we start with an informal conversation to align on expectations, then follow up with a formal written offer.
Full transparency throughout, and time for you to make an informed decision.
To keep things fully transparent and mutually fair, we complete a reference check before the formal offer is extended.
No surprises - just part of how we make careful, informed decisions on both sides.

This listing is sourced directly from PFM Global Fzco's careers page and normalized into a canonical job model.