Analytics / Data Engineer

Prop Firm Match; Town of Poland (NY); On-site; USD 39,060 - 61,380; Full time

Benefits offered by this job

Competitive compensation

Remote working flexibility

Professional growth opportunities

Job summary

Prop Firm Match is looking for a Data Engineer to own and scale the core data platform that powers reporting and analytics. This fully remote role requires strong SQL skills, experience with data pipeline engineering, and a capacity for asynchronous communication.

You will build reliable models across several business functions and improve data quality to support AI-driven workflows. Join a dynamic team that values quality and collaboration.

Qualifications

• 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).

Responsibilities

• Own and scale the core data platform for reporting and decision-making.
• Build reliable business data models across various domains.
• Improve data quality and reduce manual workloads.

Skills

Data pipeline engineering experience

Strong SQL skills

Warehouse modelling skills

Workflow orchestration tools

Excellent async written communication

Tools

BigQuery

Airbyte

dbt

Airflow

Job description

Compensation

$3,500-$5,500 / month gross

Company Overview

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 are 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.

About The Department

Data & Analytics is the function that turns raw business data into decisions. We own the data platform, product analytics, marketing attribution, and revenue operations analytics. Our current priority is building reliable data infrastructure that supports both day-to-day reporting and the next wave of AI-driven workflows at PFM.

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.

Performance Objectives

Objective 1 - Own the data platform foundation

Outcome: Reliable, well-modelled, documented warehouse data that powers reporting and AI workflows across the company.

• 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

Outcome: Trusted source of truth across revenue, attribution, product funnels, partner performance, finance, and executive reporting.

• 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

Outcome: Reduced reconciliation discrepancies; reduced manual reporting overhead across Finance, Analytics, and Partners teams.

• 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

Outcome: AI/automation initiatives scale on clean data; new sources are integrated without manual stitching.

• 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

Reporting Cadence

• Reports to: Konstantinos Kattidis, Head of Data & Analytics
• Direct reports: None
• Key cross‑functional partners: Product, Marketing, Finance, Operations, Analytics, Engineering
• Upward reporting cadence: Weekly 1:1 with Head of D&A; monthly written summary; quarterly OKR review

Location & Work Setup

• Remote, with strong overlap with CET hours (4+ hours of overlap)
• Working hours: roughly 9 AM - 6 PM CET, with reasonable flexibility
• Employment type: Full‑time

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

We provide competitive compensation, remote working flexibility, professional growth opportunities, and a collaborative, ownership‑driven culture within a fast‑moving, fully remote team.

Equal Opportunity Statement

We are an equal opportunity employer and welcome applicants from all backgrounds, experiences, and perspectives.