Data Engineer

at  ResQ

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.

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!