Analytics, Data Engineer

Job not on LinkedIn

🔥 3 minutes ago

Apply Now

Find Similar Remote Jobs

Receive Emails For Remote Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Prop Firm Match

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2023

Search, compare, and order the perfect prop firm plan for you.

📋 Description

• Own and scale the core data platform for reporting, attribution, product analytics, reconciliation, AI workflows, and decision-making. • Turn fragmented raw data into reliable, reusable business intelligence layers. • Manage BigQuery warehouse architecture and dbt models. • Oversee Airbyte pipelines and tracking infrastructure. • Apply orchestration tools for recurring workflows. • Monitor pipeline reliability and address breakages. • Build reliable business data models for trusted sources across various teams. • Improve data quality and reduce manual work through governance and automation. • Enable AI workflows and new integrations with structured data. • Collaborate with cross-functional partners such as Product, Marketing, Finance, Operations, Analytics, and Engineering.

🎯 Requirements

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

🏖️ Benefits

• Hiring stages are simple, transparent, and respectful of your time. • Application screening. • Video intro + role fit questionnaire. • Discovery HR Interview. • Real-world task based on real data challenges. • Deep-dive Professional interview with the Head of Data & Analytics. • Functional Interview with senior team members. • Peer & values conversation evaluated against PFM's structured values scorecard. • Informal conversation to align expectations before a formal written offer.