tenna - Principal Data Engineer
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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. • Full-time opportunity. • Location: Remote - nationwide. • Opportunities for growth and personal development within a highly dynamic team. • Robust, low-cost benefit packages offered. • Benefit coverage begins on the first date of employment. • Paid Time Off and Volunteer Time Off offered. • Dependent Care offered. • Employee referral bonuses.
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.
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