Data Engineer

Wheelhouse is a revenue management platform for the flex rental space, seeking a Senior Data Engineer to oversee their data ingestion engine. The role involves optimizing and managing data pipelines, ensuring the reliability and scalability of their multi-terabyte datasets, and integrating new data sources into their system.

Responsibilities:

• Architect, optimize, and supervise the daily ingestion pipelines that process calendar data for 14+ million listings
• Tune and scale our AWS RDS PostgreSQL and Aurora databases to handle extreme high-throughput read/write operations and multi-TB storage
• Optimize background job orchestration to ensure timely and efficient data processing
• Design and build robust ETL processes to integrate new, complex data sources into our ecosystem
• Collaborate with application engineers to make diverse versions and aggregations of our data easily accessible to the core application
• Apply DevOps best practices to maintain and improve our AWS infrastructure, CI/CD pipelines, and infrastructure-as-code
• Build comprehensive monitoring, alerting, and observability tooling to catch data bottlenecks before they impact the business

Requirements:

• 5+ years of Data Engineering or Backend Engineering experience, specifically dealing with massive, high-velocity datasets (multi-TB scale) and 10+ years overall engineering experience at technology companies
• Deep database expertise: Advanced knowledge of relational databases, specifically PostgreSQL and AWS Aurora. You must know how to tune databases, optimize complex queries, and manage large-scale indexing
• Strong programming skills: Proficiency in Ruby and Ruby on Rails (or a strong willingness to learn, backed by expert-level experience in a similar language like Python) to navigate our core stack
• Job Orchestration: Experience with background processing frameworks at scale (Resque, Sidekiq, Celery, or similar)
• DevOps & Cloud: Hands-on experience with AWS cloud services, infrastructure provisioning (Terraform/CloudFormation), and CI/CD pipelines
• Data Modeling: Strong ability to design data models that balance fast ingestion with efficient application querying
• Problem Solver: A track record of identifying performance bottlenecks in complex distributed systems and implementing elegant solutions
• Remote DNA: Demonstrated ability to work autonomously, communicate asynchronously, and manage your own 'healthy hustle.'