Senior Data Engineer, CookUnity

• We’re looking for someone who’s excited about the prospect of taking an existing product that’s growing rapidly and helping to rebuild key components of our system
• This will help set CookUnity up to scale gracefully for our next years of rapid growth, reduce overall system complexity, enable greater product experimentation, and enable product teams to build incredible features faster
• 7+ years of relevant industry experience
• Proficient in Java, Scala, or Python, with deep expertise in data processing tech and in writing complex SQL queries
• Proven track record of driving innovation within highly technical, distributed teams. You have driven complex projects to completion and are motivated by solving high-impact problems and building for the best user UX
• Proven track record in designing, building, and operating robust distributed data platforms (e.g., Snowflake, Spark, Flink, Kafka), and handling large data sets
• Demonstrable experience of building, productionalizing, and optimizing real-time and batch data pipelines

Desirable

• The Engineering Foundation team is a newly formed team responsible for ensuring the overall architecture supports the company’s rapid growth and provides an excellent experience for all CookUnity users
• We’re undertaking a large re-architecture of many systems across the engineering stack, and we’ll shape (and build) the future frameworks, technologies, and patterns for the rest of the engineering org to leverage
• This is a rare opportunity to work at a rapid growth scaleup company and build on an entirely net new system to set the engineering foundation and principles across the org
• As a Staff Data Engineer on the Engineering Foundation team, you’ll play a critical role in defining the direction for the future of CookUnity’s data engineering architecture
• You will design & build net new data pipelines and systems that form the future base of our B2C data engineering stack, and set in place best practices and patterns for the entire CookUnity data engineering org to adopt
• Design and build net new resilient batch and real-time data pipelines that power critical products and drive rapid business growth
• Design and build data pipelines facilitating the migration from existing disparate data models and data sources, into new data models and databases in production
• Champion data reliability and performance by implementing proactive monitoring and quality-first engineering practices
• Optimize data models to support fast, efficient decision-making across high-impact product and business use cases
• Partner closely with product, engineering, and data science teams to quickly translate evolving business needs into scalable, production-ready data solutions
• Shape the future of data engineering at scale, helping define the long-term roadmap and setting best practices as we grow
• Coach and level up teammates, fostering a culture of learning, ownership, and continuous improvement
• Demonstrate strong self-direction and thrive in environments with high ambiguity, making sound decisions even when clear solutions are not readily apparent