Analytics / Data Engineer

Prop Firm Match; Germany (OH); On-site; USD 42,000 - 66,000; Full time

Benefits offered by this job

Competitive compensation

Remote work flexibility

Professional growth opportunities

Collaborative team culture

Job summary

Prop Firm Match is seeking a Data Engineer for a full-time role focused on building and scaling data platforms. The ideal candidate will have over 3 years of experience in data engineering, strong SQL skills, and familiarity with tools like dbt and BigQuery. The position supports a remote work setup with hours overlapping CET, fostering a collaborative environment.

This role offers significant opportunities for professional growth and the chance to contribute to a cutting-edge team dedicated to enhancing data-driven decision-making.

Qualifications

• 3+ years of experience as a Data Engineer or Analytics Engineer.
• Strong SQL and warehouse modelling skills, especially with dbt and BigQuery.
• Experience with data pipeline engineering tools like Airbyte.

Responsibilities

• Own and scale the core data platform for reporting and analytics.
• Build reliable business data models for comprehensive analysis.
• Improve data quality and automate business processes.

Skills

SQL

dbt

BigQuery

Data pipeline engineering

Workflow orchestration (Airflow)

Data governance

Excellent written communication

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.