Big Data Engineer

Glassbox is looking for a Big Data Engineer to join our global R&D team.

We are Glassbox, and our mission is to reveal the insights that empower organizations to deliver exceptional digital customer experiences.

We are growing and have been recognized by G2 as one of 2024's Top 50 Software Companies worldwide.

Our customers are the best of the best, including six of the ten largest global banks, the world's largest hotel chain, the largest healthcare provider, and the largest telecommunications company in the U.S.

Now is the perfect time to come to Glassbox and help us accelerate our global leadership position!

If you are a dynamic, successful, experienced metrics-driven leader, Glassbox might be a great fit.

Will you join us on this journey?

As a Big Data Engineer, you will be pivotal in building and maintaining our Machine Learning infrastructure, ensuring scalability, reliability, and efficiency in handling large-scale data processing

What will you do?

• Design, implement, and optimize big data pipelines and workflows
• Develop and maintain scalable solutions using PySpark and other big data technologies
• Deploy and manage containerized applications using Kubernetes (K8S)
• Build and maintain data solutions on cloud platforms (preferably AWS)
• Collaborate with cross-functional teams to ensure data accessibility, quality, and security
  
  

• At least 3 years of hands-on experience in big data environments, with a strong track record of managing and scaling large-scale data processing systems
• Proficiency in Python and PySpark for big data processing
• Demonstrated expertise in designing, optimizing, and maintaining data pipelines using popular open-source frameworks such as Kafka, Spark, and Airflow, focusing on performance and reliability
• Familiarity with Kubernetes (K8S) for deploying and managing applications
• Experience with cloud platforms - AWS experience is a significant advantage
• A BSc in Computer Science, Engineering, or a related field
  
  

• Knowledge of Apache Iceberg for data lake optimization
• Experience with machine learning workflows and tools, including MLflow
• Understanding of Vector Databases (VectorDB) is a plus