Data Engineer

Wheelhouse

8d•$156,000 - $180,000•Remote

About The Position

Wheelhouse is a revenue management platform for the $500B+ flex rental space. Our technology empowers short & mid-length stay operators, who manage single-family homes, apartment buildings, and (in some cases) hotels - a broad & massive addressable market. Wheelhouse believes a more flexible & connected world is both inevitable & important, and we build technology to make sure the businesses that enable this lifestyle & society can thrive. At our core, we process massive amounts of data to give our clients a competitive edge. We track calendar data for over 14 million listings worldwide, ingesting the future calendar of availability and pricing for every single listing, every single day. This translates to a multi-terabyte, highly dynamic dataset. We are looking for a Senior Data Engineer to take ownership of this massive daily ingestion engine. Working within a Ruby on Rails and Resque environment, backed by AWS RDS Postgres and Aurora as well as Athena, you will ensure our data pipelines are robust, scalable, and highly optimized. You will not only supervise and improve our existing daily ingestion but also design systems to integrate new data sources and seamlessly deliver this data to our core application. Your mission is to guarantee the reliability, speed, and scale of our data infrastructure. You will be the technical guardian of our multi-terabyte dataset, ensuring that as we grow to track even more listings and add new data sources, our ingestion engine scales gracefully and cost-effectively without missing a beat.

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."

Nice To Haves

Works independently and takes ownership: You don't wait to be told what to optimize. You treat the data infrastructure as your own product, proactively identifying areas for improvement and driving them to completion.
Thinks in systems: You understand that scaling isn't just about writing faster code; it's about how Resque, PostgreSQL, and our AWS infrastructure interact. You see the big picture and understand the cascading effects of your changes.
Stays calm under pressure: Because this daily data sync is our lifeblood, pipeline hiccups are critical. You can troubleshoot complex, multi-terabyte issues methodically and keep a cool head when the pressure is on.
Communicates technical concepts clearly: You can easily translate complex data engineering constraints and architecture decisions into plain language for the wider engineering and product teams.
Values pragmatism over perfection: You know when to invest in an elegant, long-term architectural solution, and when the business just needs a robust, practical fix to keep the daily sync running smoothly.
Is obsessed with observability: You believe a system isn't finished until it's properly monitored. You build alerts and dashboards to catch anomalies and bottlenecks before they ever impact our clients.
Is super detail oriented: You intrinsically see that certain data problems can be needles in haystacks and you are process driven to build safeguards to flag the vast majority of issues before our customers notice the same.

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.