Level

Rebar

Software Engineer, Data Platform

AI in this role

About Rebar

Rebar is building the AI operating system for commercial HVAC, Electrical, and Plumbing.

Over the past year our quoting platform has processed tens of thousands of projects across North America and we’re continuing that growth. Our customers include many of the top firms in the industry. Some of these companies are running billion dollar construction projects on workflows that still look like it's 1985.

Construction is 10% of GDP and still massively underserved by software. We are changing that.

We recently raised a $14M Series A from leading construction tech investors and are entering our next phase of growth. We are building a set of AI native products that will define how this industry operates.

About the Engineering Org

We're in the age of ai and the role of the engineer is rapidly changing. We're aware. We're being very intentional of ensuring we adapt with it. We are fostering an engineering culture of growth and development. We strongly emphasize care of craft and winning together. Everyone operates like an owner, we find a way, and we win together.

About the Role

We’re hiring a Software Engineer to own our data platform and analytics. This will be the event infrastructure that ties our services together and makes surfacing new insights to our customers seamless.

We want to be clear that this is not a business insights or analyst role - this is a backend/systems role. You are going to be designing migrations, schemas, and the pipelines for all of the data that we can read off of extremely dense construction plansets.

Responsibilities

  • Design and architect real time data ingestion

    • We have hundreds and soon will have thousands of ML jobs running at any given time processing dense construction documents. We parse and extract lots of information about these projects. This information should be ingested in real time for greater insights for our customers as well as for our internal team.

  • Consolidate and cleanse our existing data architecture

    • This data is inherently messy. We need clean data schemas for this as we grow and evolve. You should be designing with our entire system in mind.

  • Set up the data platform for agentic layers

    • Providing context to our Rebar Agent is a pillar of having a world class agent. You will be fundamental in this role

  • Data platform for developer velocity

    • Finally, you are setting up the backbone of our data platform so that other engineers can access and query the data they need with ease.

What We’re Looking For

We’re looking for a passion and excitement about large amounts of structured and unstructured data. You should eat and breathe your domain and be hungry for it. We want curious engineers that love the research part of the job. Interested in trying DuckDB? Or just want to mess around with parquet files some? This could be your chance to try it. Always wanted to explore the cost benefit analysis between Cassandra, DynamoDB, and Scylla? Or intrigued by balancing a local analytics platform that minimizes latency and network load? You might have found your role.

We want someone that has experience dealing with vastly more data than we currently have because that is the direction that we’re moving. You should be prepared to work hard (we are still a Series A startup), take a risk, learn a shit ton, and grow individually and with us as a company.

Qualifications

  • 5+ years of industry software engineering experience

  • experience with data intensive systems in productions

  • ideally you will have handled complex data migrations for active clients

  • knowledge of various databases and indexes (Postgres/Aurora preferred)

  • experience justifying data architecture tradeoffs

Nice to Have

  • Event-driven / streaming pipeline experience.

  • Analytics modeling (materialized views, rollups, columnar/OLAP engines)

  • Experience with workflow orchestration (temporal is what we use)

  • Worked in a small, high-ownership engineering team where you set the standard rather than inherited one.

Compensation and Benefits

  • Salary: Competitive base salary

  • Equity: Meaningful equity package, commensurate with experience

  • Benefits: Comprehensive medical, dental, and vision coverage

  • Perks:

    • agentic tooling budget

    • lunches provided, dinners provided (after a set time)

    • great culture and office banter

This is a salaried, onsite role located in New York City's Flatiron district. We are still a startup! We love working onsite together and believe strongly that this gives us for creative problem-solving, and building strong connections. You'll be at the heart of our fast-paced operations, actively contributing to a culture that values engagement, growth, and teamwork.

How we rate this

Software Engineer, Data Platform at Rebar rates 23 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

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