Principal Data Engineer

Tenna is a company rooted in the construction industry, providing innovative solutions for managing and tracking construction equipment. The Principal Data Engineer will own the data architecture across the connected equipment platform, designing systems and overseeing engineering teams to ensure data infrastructure supports the company's growth.

Responsibilities:

• 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
• Designs the IoT data ingestion and distribution architecture to support data from a significantly expanding device fleet, including replayability, aggregation, and real-time distribution patterns
• Tests, evaluates, and recommends technologies to improve our overall data infrastructure
• Produces excellent documentation

Requirements:

• 12+ years of professional data engineering or software development experience; self-motivated and driven to deliver impactful data products
• 2+ years' experience providing architectural direction and design oversight to engineering teams, not just individual mentorship. Excellent communication skills are a must
• Experience setting data architecture standards and providing technical oversight across multiple engineering teams
• Bachelor of Science in Computer Science, Data Engineering, or equivalent experience; intimately familiar with the fundamentals of computer science, data architecture, and distributed systems
• Substantial experience with SQL; experience with NoSQL is a plus
• Experience with Python for data engineering workflows; experience with Node.js is a plus
• Experience with distributed data processing frameworks such as Apache Spark or Apache Flink is a plus
• Experience with data orchestration tools such as Apache Airflow or similar is a plus
• Experience with containerized application deployments, especially using Docker, is highly preferred
• Experience with large-scale data systems and data warehousing solutions is highly preferred; possesses in-depth knowledge of the open source data ecosystem and how to incorporate it into scalable solutions
• Experience with message queueing architectures, especially RabbitMQ, is preferred
• Experience with Amazon Web Services, especially S3, RDS, DMS, and VPC; experience with Redshift or EMR is a plus
• Experience working with AI/ML systems, including building data infrastructure to support model training, inference pipelines, or AI-powered features, is a plus
• Experience designing data architectures for IoT or high-frequency telemetry systems is highly preferred