Patreon

Staff Software Engineer, Data

Patreon3 months ago
Location

Remote

Workplace

Remote

Type

Full Time

Salary

USD 257,500 – 386,000

Level

Staff

Role

Staff Software Engineer

Posted

Dec 9, 2025

Full TimeRemoteStaff

The role

Summary

Patreon is seeking a Staff Software Engineer for its Data Engineering team to architect and scale critical data infrastructure that powers creator analytics, ML systems, and strategic decision-making. The ideal candidate will design robust data pipelines, develop scalable data models, and drive data quality and reliability across the organization.

What you'll do

Data Pipeline Architecture: Design, build, and maintain comprehensive data pipelines that support ingestion from production databases, object storage, message queues, and external vendors into the Data Lake
Data Modeling: Develop intuitive, performant, and scalable data models including facts, dimensions, and aggregations to support product features, analytics, experimentation, and machine learning workloads
Pipeline Implementation: Implement robust batch and streaming data processing pipelines using Spark, Python, and Airflow, handling complex scenarios like incremental processing and late data handling
Data Quality Management: Define and enforce standards for data accuracy, completeness, lineage, and dependency management, with a focus on building monitoring and observability systems
Cross-Functional Collaboration: Work closely with Product, Data Science, Infrastructure, Finance, Marketing, and Sales teams to transform ambiguous questions into well-scoped, high-impact data solutions
Technical Excellence: Pay down technical debt, improve automation, drive best practices in data modeling, testing, and reliability, and mentor peers in data engineering

What we look for

Technical

Data Processing ToolsExpert-level proficiency in distributed data processing tools like Spark, Flink, Kafka Streams
Programming SkillsStrong programming foundations in Python with understanding of software engineering design patterns and principles
Data InfrastructureExpert knowledge of modern data lakes (Delta Lake, Iceberg) and familiarity with data warehouses and various production data stores

Education

Academic BackgroundBachelor's degree in Computer Science, Computer Engineering, or related field, or equivalent professional experience

Experience

Professional Experience6+ years of software development experience, with at least 2+ years building production-grade data pipelines
Data ModelingUnderstanding of data modeling and metric design principles

Skills

Required skills

SQLExpert-level proficiency in SQL and distributed data processing
PythonStrong programming skills with software engineering best practices
Data LakesExpertise in modern data lake technologies

Nice to have

Machine LearningExperience with data pipelines supporting ML systems
Cloud TechnologiesFamiliarity with cloud data storage and processing platforms

Compensation & benefits

Salary

USD 257,500 – 386,000 (annual)

Stock options

Available

Benefits

Healthcare

Comprehensive health insurance coverage

Equity

Stock option plans for long-term value creation

Flexible Time Off

Unlimited or highly flexible paid time off policy

Learning Stipend

Financial support for professional development and learning

Parental Leave

Comprehensive parental leave benefits

401k

Retirement plan with company matching

Remote Work

Flexible remote work arrangement with optional office attendance

Lifestyle Stipend

Additional financial support for personal well-being


Interview process

  1. 1
    Initial Screening Phone or video call with recruiting team to discuss background and role fit
  2. 2
    Technical Screen In-depth technical interview focusing on data engineering skills, system design, and problem-solving
  3. 3
    Hiring Manager Interview Detailed discussion about team dynamics, role expectations, and candidate's experience
  4. 4
    Technical Challenge Hands-on coding or design challenge related to data pipeline architecture and implementation
  5. 5
    Team Interviews Multiple interviews with potential teammates to assess collaboration and cultural fit
  6. 6
    Final Interview Comprehensive review with senior leadership and potential offer discussion

Apply for this position

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