Flat (S20)
We’re the Opendoor of Mexico. We buy homes with an instant offer, fix them up and sell them.

Data Engineer

Mexico City / Remote
1+ years
About Flat

Our mission is to provide liquidity and help people buy and sell homes quickly and in a transaction free of stress

Why Join us at Flat.mx?

We are a proptech startup located in Mexico City: We launched in May 2019 and are a fast-growing team of motivated people (techie guys, developers, designers, real estate specialists) working together, spending time designing and building Flat, and, of course, having lots of fun. At Flat we have a passion for building a innovative products. We are looking to expand our team with dedicated, fast learners who are willing to roll their sleeves up and make things happen, in other words, people who are driven by learning on the fly.

About the role

Skills: Python, Amazon Web Services (AWS)

Data Engineer

Flat is flipping the way homes are sold in Mexico. With a deep layer of technology and data, Flat simplifies the painful process of buying or selling a home. With Flat, sellers are able to sell their homes for a fair price in a matter of days, and move-in to a new apartment effortlessly. For buyers, Flat guarantees the conditions of the property, a fair purchase price, and a seamless buying experience. We are driven by the challenge of disrupting a large industry that hasn’t seen much innovation in the past recent years.

Job Description This position is part of a growing Data Science area in Flat that builds and refines Data Science tools and techniques. As a Data Engineer, you will shape the future of what data-driven organizations look like, drive processes for extracting and using that data in creative ways, and will enjoy seeing your insights turned into real products.


  • Expand and optimize our data and data pipeline architecture, as well as optimizing data flow and collection for our teams.
  • Assemble large, complex data sets that meet business requirements.
  • Build the infrastructure required for automated optimal extraction, transformation, and loading of data from a wide variety of data sources using Python, SQL and AWS tools.
  • Build analytics tools and provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
  • Identify opportunities to improve our models.
  • Develop strategies to capture data on buyer preferences.


  • We are looking for a candidate with 2+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics,Information Systems or another quantitative field. They should also have experience using the following software/tools:

  • Good understanding of shell commands and scripting for automation (Bash)

  • Understanding of statistical concepts

  • Proficiency in SQL, numerical programming and data wrangling in Python

  • Experience building RESTful APIs

  • Experience with relational SQL and NoSQL databases

  • Experience with AWS cloud services: S3, Lambda, RDS, ECS, ECR.

  • Experience with DevOps tools (GitHub)

  • Experience with Container technologies (Docker)

Nice to have

  • Experience using Luigi, Airflow or Apache NiFi
  • Excellent verbal and written communication skills
  • Creative thinking and exceptional problem solving skills
  • Previous experience in the PropTech ecosystem


We’ve built an in-house CRM using Python + Django, with PyTest as a testing tool. Our frontend is built with ReactJS, using Selenium + Cypress as testing tools. Our tools for scouts are built as web mobile apps using VueJS. We use Docker to run our code on AWS using EC2 + Docker-compose, and we have a full CI/CD pipeline using CircleCI.

We have several interesting problems at the moment: how to efficiently retrieve enough trustworthy housing data to buy/sell and build a robust data model for pricing. For this, we’ve built several scraping and broker management tools, a single source of truth for housing data, and several connections with external pricing models. We expect to bring all of our operations under our CRM in the next 6 months, away from our current mix of tools.

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