About Ubeya

Ubeya is a leading B2B SaaS platform built for the workforce industry, making it easy to manage complex operations at scale. From major stadiums to high-profile sports and entertainment events, Ubeya powers staffing for Football, Basketball, Baseball, Racing, and more — helping top venues deliver seamless, unforgettable experiences.
Our workforce management platform enables hundreds of businesses and staffing agencies worldwide to stay resilient and adaptable in a fast-changing world — driving growth, operational excellence, and a happier, more engaged workforce.

The Role

We are looking for an experienced Data Engineer to join our growing team. As part of our R&D efforts, you will play a pivotal role in designing and building scalable data pipelines and infrastructure, ensuring reliability and efficiency across the full data lifecycle. Your work will have a substantial impact on our product experience and the business.

What You will do:

Design and build scalable data architectures and pipelines, ensuring reliability and efficiency across the full data lifecycle.
Optimize and manage data infrastructure, enabling analytics, machine learning, and real-time applications.
Develop orchestration and monitoring frameworks to support complex workflows.
Prepare, transform, and serve data for AI/ML models, ensuring quality, accessibility, and performance.
Collaborate with engineers, analysts, and data scientists to support data-driven decision making.
Implement and enforce best practices for data governance, quality, and security.

Who you are:

5+ years of proven experience as a Data Engineer or in a similar role, with at least 2+ years delivering production systems.
Strong proficiency in Python for data processing and automation.
Deep knowledge of SQL and data modeling.
Experience with workflow orchestration tools such as Airflow or Dagster.
Experience with cloud platforms such as GCP, AWS, or Azure.
Familiarity with modern data warehouse solutions such as Snowflake, BigQuery, or Redshift.
Experience developing and optimizing ETL/ELT pipelines and transformations.

Bonus Points

Experience with real-time data streaming technologies (e.g., Kafka, Flink, Spark Streaming).
Exposure to NoSQL databases (e.g., MongoDB, Elastic, Redis).
Familiarity with MLOps and deploying machine learning models in production.
Knowledge of CI/CD and infrastructure-as-code.
Experience with Node.js or working closely with backend engineering teams.
Familiarity with AI orchestration tools such as LangChain.
Prior experience in fast-paced startup environments.