Principal Data Engineer (Remote)

ezCater is the most trusted provider of corporate food solutions and is purpose-built for business. ezCater's corporate food platform and flexible, scalable food solutions allow organizations to centralize and track their food spend, and fulfill everything from daily employee meals to client meetings and company all-hands. ezCater backs this up with business-grade, best-in-class, customer service and an unmatched nationwide footprint. We're backed by top investors including Insight, Iconiq, Lightspeed, GIC, SoftBank, and Quadrille.

Are you passionate about data? How about leveraging data to drive meaningful impact across a fast growing two-sided marketplace? Have opinions on how to best enable data scientists across a billion-dollar company to do elastic workforce planning or real-time customer lifetime value prediction? Then we should definitely talk!

The Data Technology team at ezCater is growing! As we look towards 2023 and beyond, data is a key strategic component across the company - from advanced, real-time machine learning to business intelligence and data governance. Data is our differentiator and how we will drive real, meaningful impact to the $60+billion Catering industry.

We are hiring a Principal Data Engineer to join our expanding team in solving complex data and platform challenges to accelerate our growing business. The ideal candidate lives and breathes data while driving systems and architecture best practices. They care about driving business impact through producing solid and efficient infrastructure alongside accurate and performant data.  You will have the opportunity to work directly with executive stakeholders as we embark on a massive-scale data modeling effort across the organization, so flexibility and the ability to translate business requests to implementation are key. 

What you’ll do:

• Own the technical and architectural direction of our enterprise data warehouse, including: data ingestion, data platform, foundational data, curated data marts and data activation
• Partner with stakeholders to drive data needs across: analytics, machine learning, data science, and master data management
• Provide guidance, technical expertise and reference architecture to our data teams on architecture best practices, standards, methodologies
• Design and lead the development of high-performance data pipelines
• Partner with cross-functional teams to define data requirements, design data models, and implement data solutions that meet business needs
• Align our technology with the goals of the business and strategic objectives
• Monitor data systems to ensure quality and availability while seeking to drive down costs
• Coach, mentor and up-skill data engineers in architecture skills and thinking
• Actively maintain and build a culture of learning, respect, transparency, and trust
• Facilitate technical discussions across teams, organizations, and technology stacks
• Work with engineering leads and Product Managers to define data architecture and build prototypical software stack
• Communicate cross functionally to drive alignment across data, engineering and product
• Align data architecture and systems with regulatory requirements, data privacy, and security standards
• Assist in building data governance processes, policies, and procedures
• Conduct research on emerging technologies and trends in the data & machine learning architecture space and recommend improvements to existing architecture
• Champion engineering and operational excellence, establishing metrics and process for assessment and improvements

What you have:

• 10+ years of experience in data architecture, data modeling and data management, with specific expertise on scaling data systems
• Experience across modern cloud based data ecosystems. AWS and Snowflake experience preferred
• Strong knowledge of data architecture best practices, data modeling tools, and ELT/ETL processes
• Solid understanding of architectural design patterns and strategies with cloud-based data architecture, data lakes, data lakehouse, data mesh and data warehousing
• Track record of technical leadership via collaboration, mentorship, and leveling up teams
• Ability to create analysis and quick prototypes for different implementation alternatives on data ecosystems
• Our stack is Snowflake, dbt, Fivetran, Airflow, AWS, Sagemaker, MLFlow, Kubernetes + Docker, Monte Carlo, Hightouch and Python for custom ETL and data science integrations. Experience with the above is a nice-to-have, but a desire to learn is a must.
• A sharp