Principal Data Engineer

At Tenna, we believe the best is right in front of all of us and that each day holds more potential than the one before.

We believe that every new discovery can lead to something better than we thought possible.

When we boil it down, the top five qualities that define the Tenna Team are quality-obsessed, gritty, continuous learners, collaborative problem solvers, and just plain awesome.

Sound like you?

Join us as we empower our customers to control their mixed assets on one comprehensive platform anytime, anywhere.

At Tenna, we believe the best is right in front of all of us and that each day holds more potential than the one before.

We believe that every new discovery can lead to something better than we thought possible.

When we boil it down, the top five qualities that define the Tenna Team are quality-obsessed, gritty, continuous learners, collaborative problem solvers, and just plain awesome.

Sound like you?

Join us as we empower our customers to control their mixed assets on one comprehensive platform anytime, anywhere.

• Owns organizational-wide data architecture, defining standards, patterns, and designs that our teams will implement. Solves complex data challenges regardless of perceived ambiguity or degree of clarity.
• Reviews data-related designs and implementations across teams for architectural consistency, performance, and scalability.
• Produces reference implementations, proofs of concept, and hands-on guidance when teams encounter complex data engineering challenges.
• Designs and develops data pipelines, integrations, and platform features with performance and scalability in mind.
• Builds and maintains data APIs and ingestion systems that can handle complex, high-volume data efficiently.
• Takes responsibility for the quality of data systems across the organization, including testing strategies and data integrity standards.
• Owns the data architecture strategy across the platform, including database design patterns, data API standards, and data flow architecture.
• Consults with product managers to define, scope, and plan new data features and capabilities.
• Partners with the CTO and engineering leadership on strategic data initiatives and long-term architectural direction.
• Partners with teams to define data quality standards, automated data validation patterns, and testing strategies for data pipelines.
• Partners with engineering and product teams to design and support data infrastructure for AI/ML initiatives, including model training pipelines, feature stores, and inference data flows.