
11 - 50 employees
🏭 Manufacturing
📦 Logistics
🤖 Artificial Intelligence
💰 $1.2M Venture Round on 2022-05
Manufacturing • Logistics • Artificial Intelligence
Pattern is a company focused on revolutionizing air logistics through advanced automation and robotics technologies. With a commitment to bringing harmony to the logistics sector, Pattern develops sophisticated tools that enhance visibility and reliability in dynamic environments, such as airports and cargo handling. Their expertise spans across robotics, computer vision, and artificial intelligence, ensuring scalable solutions at a cost-effective price point.
🕒 October 29
Where this job comes from
Posted on Pattern's careers page ↗, not through a job board
First seen by Remote Rocketship October 29
Still open on Pattern's site. Checked 4 minutes ago.

11 - 50 employees
🏭 Manufacturing
📦 Logistics
🤖 Artificial Intelligence
💰 $1.2M Venture Round on 2022-05
Manufacturing • Logistics • Artificial Intelligence
Pattern is a company focused on revolutionizing air logistics through advanced automation and robotics technologies. With a commitment to bringing harmony to the logistics sector, Pattern develops sophisticated tools that enhance visibility and reliability in dynamic environments, such as airports and cargo handling. Their expertise spans across robotics, computer vision, and artificial intelligence, ensuring scalable solutions at a cost-effective price point.
• Expand and optimize PatternAI's data pipeline architecture • Optimize data flow and collection for cross-functional teams • Build and deploy data pipelines powering PatternAI's machine learning platform • Develop warehouse architectures integrating data from diverse sources • Design analytics solutions for product development and internal collaborators
• A minimum of 4 years experience in data engineering, analytics engineering, or software engineering with an emphasis on large scale data management and processing systems • Proficiency in Python and advanced SQL • Advanced experience with ETL pipelines, data modeling and managing data warehouses (Snowflake, BigQuery, Redshift, etc) • Experience with SQL RDBMS such as MySQL, Postgres, Oracle, SQL Server, etc., as well as NoSQL systems such as MongoDB is required • Experience with tools including Meltano, dbt, Airflow, and Superset is required • Experience with Docker, Git and AWS (EC2, ECS, S3, Step Functions, and Athena) • Analytics and Business Intelligence knowledge is highly preferred • Experience working with common SaaS APIs (such as CRMs) is preferred
• Employees can work remotely
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