Data Engineer

Miami, Florida

ResQ

ResQ is a facility management platform purpose built for restaurants to streamline their repair and maintenance operations.

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ResQ 
was founded with the belief that restaurant operators and service providers should have a much better way to operate their businesses. As a first step towards our mission, we have built a SaaS-enabled marketplace that helps fast-growing restaurants manage their 🛠 repairs and maintenance, empowering them to focus on their customers.

Repair and maintenance is the heartbeat of any restaurant's operations, yet the existing management methods are complex, expensive, and time-consuming. With ResQ, restaurants can simply get connected to qualified service providers, submit jobs, track progress, and pay, all in one place.

We are trusted by the world's leading restaurant brands and are venture-backed by top-tier global VCs - and we are just getting 🚀 started!

Hello 👋 Future ResQer! 

ResQ is looking for a Data Engineering to join our Engineering team and help us take ResQ to the next level 🚀.

As a Data Engineer joining ResQ, you will play a pivotal role in driving the strategic direction of our product line. You’ll generate actionable insights and maintain reliable, scalable data pipelines that support data-driven decision-making across teams. Your expertise will be crucial in guiding the product development organization to collect data for analysis and experimentation.

We understand that joining a team is one of the most important choices you make, and adding a team member is one of the most important choices we’ll make. We want you to get to know us, and we want to understand how you approach problems, learn, and what motivates you.

What you will do:  

  • Build and Maintain Data Pipelines: Design, develop, and optimize ETL pipelines using tools like Airflow or similar workflow orchestration systems. Ensure data reliability and efficiency for downstream analytics and reporting needs.

  • Data Modeling and Transformation: Implement and maintain data models in DBT (or similar), ensuring data consistency, quality, and readiness for analysis. Develop and manage transformation workflows to support scalable data warehousing.

  • Data Warehousing and Storage: Work within cloud data warehouses (such as Google BigQuery) to ensure optimized data storage and retrieval. Develop best practices for data warehousing, focusing on cost efficiency and performance.

  • Collaboration and Support: Partner with data analysts, product teams, and stakeholders to understand data requirements and translate them into technical solutions.Provide guidance and support for data-driven projects, ensuring the right data is available for business insights.

  • Monitoring and Optimization:Implement monitoring tools to ensure data quality and pipeline health, proactively troubleshooting issues. Continuously optimize data processes for efficiency, scalability, and cost-effectiveness.

  • Documentation and Best Practices: Document data processes, models, and workflows to ensure clarity and transfer of knowledge within the team. Promote best practices in data engineering and data governance.

Who You Are:  

  • Bachelor’s degree in Computer Science, or a related field, or equivalent experience. 

  • 3+ years of experience in data engineering or a related role within a tech environment.

  • Proficiency in data technologies such as SQL and DBT, and in programming in Python.

  • Proficiency in SQL, Python, and cloud-based data warehousing tools; familiarity with DBT, Airflow, and BigQuery (or similar).

  • Proven experience in working with cross-functional teams and presenting data-driven recommendations to senior stakeholders.

  • Strong understanding of product development processes.

  • Exceptional problem-solving skills, attention to detail, and ability to thrive in a fast-paced, dynamic environment.

Nice To Haves:

  • Knowledge of machine learning and inference, including data mining.

  • Experience with dashboarding tools such as and Looker (or other BI tool) 

How you will do it:

  • A self-starter: You wake up, form a plan, and get going!

  • Practice Extreme Ownership - including exhibiting a bias for action, a deep desire to understand all parts of our business, including our customers, and partners; taking risks, adapting and learning till you succeed; a mindset to persevere!

  • Be open to feedback; listen, learn, and iterate. We’re all One Team!

What to expect as a candidate:

While we are never perfect, we have aimed to build a process that fosters fairness and helps to minimize bias, this includes structured processes and interviews. Our goal is that everyone interviewed has a positive experience, regardless of the outcome.

Stage 1️⃣:  Send us your resume and a note about how your story connects to ours. Feel free to focus on what you have learned rather than just a list of responsibilities. Tell us your story! We’ll aim to tell you quickly if it is not the right fit so you are always informed.

Stage 2️⃣: Successful candidates will meet with our Talent lead. It will be standardized to keep things fair but also with enough room to show your uniqueness. We’ll communicate the salary range now for full transparency. If you like us and we also think there is a fit, we’ll invite you to the next stage.

Stage 3️⃣: A call with our Co-Founder/Head of Engineering who will ask you more in depth questions about your experience and skills. Come with questions! 

Stage 4️⃣: This stage will be an opportunity to meet a member of our Data team. This will be a great opportunity for you to get a glimpse into your day to day at ResQ and understand the different projects you may work on. 

Stage 5️⃣: This round will be a technical case study interview, this will be a panel style interview and will include a few members from our engineering team. 

Stage 6️⃣: This is the final stage in the process where you will meet our CEO, KJ. This stage will be more of an introductory call and less focused on your in depth skills and knowledge. KJ will share with you more about ResQ’s vision and mission. He will also ask you some more questions and he will, of course, be able to answer any additional questions you might have.

Want to learn more? 👀 Keep Reading!

We are a mission-driven team and have a big vision to revolutionize the service industry. While on that journey, we recognize that building a startup is very hard. Turning vision into reality in a fast-growing environment takes superhuman efforts and is often one of the most difficult, yet rewarding, things one can do.

We do our best to ensure transparency during all stages of the interview process but we realize it's a lot of information 📚 to take in at once so we wanted to centralize everything to make it easier for you to navigate through. We have created a Talent Notion page which will help you learn more about us during the recruitment process.


We are spilling the Tea 🫖 on all things ResQ, click here if you want access to the inside scoop 💬 Tell your friends, because sharing 🫶 is caring 🧡

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ResQ strongly believes that diversity of experience, perspectives, and background will result in a better environment for our employees and a better product for our users. ResQ is an equal opportunity employer. We do not discriminate against applicants based on race, colour, religion, sex, national origin, or disability, or any other status or condition protected by Ontario or local law. ResQ is committed to workplace diversity and will provide accommodation to applicants with disabilities throughout the hiring process.

Not Sure You Meet all the Requirements? We know the
confidence gap can get in the way of meeting spectacular candidates, so please don’t hesitate to apply — we’d love to hear from you!

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Job stats:  2  0  0
Category: Engineering Jobs

Tags: Airflow BigQuery Computer Science Data governance Data Mining Data pipelines Data quality Data Warehousing dbt Engineering ETL Looker Machine Learning Pipelines Python SQL

Perks/benefits: Startup environment Transparency

Regions: Remote/Anywhere North America
Country: United States

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