Principal Data Engineer

Principal Data Engineer

Dallas or Chicago – hybrid WFH

Summary

This role will focus on owning both the architecture and engineering for a new enterprise-grade analytics platform. The goal of the system is to provide better insights as it relates to real estate investments and asset management, for both internal and external customers. You'll work with key stakeholders to understand the business goals, and then spent approximately 20% of your time designing a solution, and approximately the other 80% of your time engineering the solution. As a Principal, you'll have the autonomy to make key technology decisions, and have significant influence over the product roadmap. You'll have the ability to make an impact on a highly visible project, and get the opportunity to work with other talented Data, Software and DevOps engineers. To summarize our tech environment at a high level, we primarily run Snowflake on Azure, and use Python and Spark extensively.

What you'll be doing

• Work on a range of product initiatives on a rotational basis, which require special engineering and architectural guidance
• Provide architectural guidance on the most important technical projects within the organization
• Actively mentor and positively influence the teams you'll be working with, in particular junior engineers
• Actively contribute to the code bases and software development activities for the initiatives you will oversee
• Own and develop the architectural standards and collaborate on technical vision-setting in conjunction with the VP, Engineering, Tech Leads, and Product Managers
• Work in close collaboration with product management to ensure software is developed that anticipates future needs and maintains option value

Skills we're seeking

• 10+ years of experience with Data and/or Software Engineering
• Must have strong experience with data engineering in cloud-environments
• Must have strong experience with cloud-based DWs, ideally Snowflake
• Must have experience using modern data engineering tools and techniques, ideally with Python and Spark/PySpark in your stack
• Experience with data modeling

Nice to have experience

• Azure experience
• Experience building out "data platforms" or "data products"
• DevOps experience