Staff Data Engineer

Ubiety Technologies, Inc is building a cutting edge AI platform capable of generating world first insights from high velocity Radio Frequency data that will improve the safety and security of homes, businesses, and communities.  We offer a fast-paced, highly collaborative startup environment where you will be inventing and developing transformative products to improve the lives of our customers.  You will be working alongside extremely talented engineers and creative designers from inception through delivery of a revolutionary product.

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We’re looking for a Staff Data Engineer to join Ubiety’s growing Data Team. This is an opportunity to lead the development of a cutting edge, high velocity, and high volume data streaming platform that consumes raw RF data from the world and connects it to our AI capabilities to generate novel insights. This role will contribute directly to building, optimizing, and scaling Ubiety’s data and AI platform effectively as we grow our customer base. This role reports to Ubiety’s Director of Data Science as a member of the Data Team and will regularly collaborate with the wider Ubiety Engineering team.  You will have a significant amount of autonomy and responsibility to own and drive the work.  Projects will vary but you will have the opportunity to work with colleagues both across the Data Team and across the wider Engineering team (Backend, Cloud Infrastructure, Embedded/Data Collection, etc).

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Standard Salary Range: $170k - $190k annually plus equity

• BS or MS Degree in Computer Science or related technical field
• 5+ years experience in relevant role (data engineering, software engineering, etc)
• Excellent development skills with one or more languages: Python/Go/Rust/Scala/Java
• Extensive experience working with SQL and NoSQL databases (Postgres, Snowflake, Redis, Cassandra)
• Strong experience with streaming data and relevant tools, including building real time data streaming applications (e.g. Apache Kafka, Flink, Beam)
• Experience working with and building data pipelines to support Machine Learning models and online inference, especially with high-velocity streaming data to generate real-time insights
• Experience building metrics and dashboards for monitoring the health and throughput of data streaming pipelines historically and in real-time
• Strong background working in cloud environments using relevant services, including building cloud-native applications (AWS and/or GCP)
• Experience with version control, Git workflows, CICD pipelines
• Experience with performance optimization and load testing a plus
• English language proficiency

• Take ownership and lead the development of our data streaming platform - including everything from research/ideation, experimentation, testing, and implementation
• Maintain and optimize existing data pipelines to identify and remove bottlenecks, reduce inefficiencies, and prepare for massive scale
• Work with the wider engineering team to audit and improve our existing data pipelines and data management practices
• Drive decision making around database/storage solutions, data retention, and data handling. 
• Work closely with our Data Scientists to aid in the development of our core analytical engine
• Write, audit, and improve our test coverage across all data pipelines and data products
• Drive and improve data literacy across the entire company

• A small, tightly-knit team that cares about each other, and cares about leveling everyone up together!
• A high level of autonomy, and opportunity to take as much of a leadership role as you are interested in
• A highly collaborative environment with an extreme level of transparency and visibility at all levels of the company
• A true meritocracy - we care about deliverables, not drama or politics.  We’ve got too much to do!
• Competitive salary with equity ownership of a fast-growing company
• Continuous learning courses and training offered to all employees
• Subsidized health care coverage 
• Flexible schedule
• Unlimited PTO policy - Work hard, deliver on your goals, and then take the time to play hard, disconnect, and recharge.