Senior Data Engineer/ Data Engineering Architect

Designlibro•San Jose, CA

14d•$120,000 - $180,000

About The Position

Since 2019, Petlibro has designed products for the intertwined lives of pets and their people. From smart feeders with health insights to ultra-filtered automatic fountains, our award-winning products are engineered to magnify the bond between your pet and you. Designed better for your lives together

Requirements

Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
5+ years of proven experience in data engineering, with a strong focus on data warehousing and data system architecture.
Expertise in design and build IoT data systems.
Expertise in architecting that power high-volume consumer application.
Expertise in big data and streaming technologies (Python, Java, Kafka, Spark,Spark Streaming).
Expertise in moderen database technology (MongoDB, ElasticSearch, StarRocks, S3, Snowflake, Bigquery etc).
Experience with data annotation tools and processes for machine learning datasets.
Familiarity with MLOps practices and tools for managing AI model lifecycles.
Knowledge about deploying systems into a production Cloud Native Environment (AWS or similar).

Nice To Haves

Experience in Java Spring Framework is a plus
Experience with video data handling and image processing is a plus

Responsibilities

Design robust and scalable data system architecture to collect, process, and store large volumes of data from IoT devices.
Design and build data systems that support real-time, customer facing data applications, ensuring data integrity and efficient retrieval processes.
Design and build a data validation framework to guarantee the accuracy and consistency of data across all stages of the pipeline, ensuring reliable insights and decision-making.
Implement data architectures to continuously improve AI models through automated feedback loops and data collection processes.
Optimize data processing workflows for AIoT tasks.
Collaborate with product owners to translate data requirements into actionable data engineering solutions.
Collaborate with other engineers, product owners to solve challenging problems.
Evangelize software engineering best practices and lead by example.