Staff Data Engineer

About The Role

We’re seeking an experienced Staff Data Engineer to lead the design and buildout of Lob’s next-generation unified event tracking platform. The consolidated platform will feed a diverse set of use cases, including both customer-facing analytics and internal operational mail tracking. You will work with your colleagues on the Data, Engineering, and Product teams to design the new platform and lead the transition away from the old. You will also coach and mentor engineers on your team and drive us to raise the bar on trustworthiness for the entire data ecosystem.

Some projects to get excited about:

• Collaborate with colleagues in the Data, Product, and Engineering teams to unify Lob’s foundational data ecosystem and enable the buildout of internal and external data products


• Create modular, reusable frameworks to enable other engineering teams to publish events to the unified platform


• Implement thorough monitoring and alerting to ensure the health of the data platform


• Apply software development best practices to ensure maintainability of the platform


• Partner with the Engineering Manager to set the Data team’s roadmap & define team processes


• Coach and mentor mid-level engineers on the Data team regarding technical best practices and problem-solving
  
  


• As a Staff Data Engineer, you’ll...

• Create and maintain documentation for data products and systems


• Advise stakeholders on the constraints and assumptions of the data processed through the unified data platform


• Deprecate outdated legacy systems without negatively impacting core functionality for end users


• Monitor Cloud and SaaS spend for unusual spikes and seek out opportunities to save costs


• Participate in the team on-call rotation (approximately 1 in 4 weeks). Triage and resolve alerts as needed


• Coordinate with other Staff+ engineers on the broader the tech team to align decision making and execute strategic initiatives

What you will bring to this role...

• Bachelor’s or Master’s degree in a quantitative field, or equivalent work experience


• At least 8 years (but preferably 10 or more) of combined experience in Data, ML, and/or Software Engineering


• Expertise in Cloud Data Warehousing (Snowflake strongly preferred, Redshift is a plus)


• Expertise in streaming data processing systems such as Kafka and Apache Flink 


• Expertise in modern software development fundamentals including APIs, version control, containerization, and CICD


• Expertise in a variety of database types, including transactional databases (PostgreSQL preferred) and document/vector databases (like Elasticsearch), with ability to select the right tool for a given job


• Familiarity with dbt (data build tool)


• Familiarity with pipeline orchestration engines (Apache Airflow or Prefect preferred)


• Familiarity with Change Data Capture (CDC) patterns and methods


• Excellent verbal, written, and visual communication skills


• Excellent organizational and project management skills


• Ability to be decisive & adaptable in the face of ambiguity


• Experience with AI-assisted coding tools like ClaudeCode or Cursor


• Proficient with project management tools including Jira

Since great engineers come from a variety of backgrounds, it doesn’t particularly matter if you have a specific degree—we want to hear about your contributions in a real-world setting.

Compensation information

The compensation for this role consists of a base salary + additional RSUs.

Annual Base Salary: $175,000- $200,000

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