Sr Data Science Engineer

Sabre is a technology company that powers the global travel industry. By leveraging next-generation technology, we create global technology solutions that take on the biggest opportunities and solve the most complex challenges in travel. 

Positioned at the center of the travel, we shape the future by offering innovative advancements that pave the way for a more connected and seamless ecosystem as we power mobile apps, online travel sites, airline and hotel reservation networks, travel agent terminals, and scores of other solutions.

Simply put, we connect people with moments that matter.

Team Description

Sabre is seeking a talented senior software engineer full Senior Data Science Engineer for SabreMosaic Team.

At Sabre, we’re passionate about building data science and data engineering solves problems. In this role you will plan, design, develop and test data science/data engineer software systems or applications for software enhancements and new products based on cloud-based solutions.

Role and Responsibilities:

• Develops, codes, tests and debugs new complex data driven software solutions or enhancements to existing product
• Designs, plans, develops and improves applications using advanced cloud native technology
• Works on issues where analysis of situations or data requires an in-depth knowledge of organizational objectives. Implements strategic policies when selecting methods, techniques
• Encourage high coding standards, using best practices and high quality
• Regularly interacts with subordinate supervisors, architects, product managers, HR, on matters concerning projects, or team performance. Requires the ability to change the thinking of, or gain acceptance from others in sensitive situations, without damage to the relationship
• Provides technical mentorship and cultural/competency-based guidance to teams
• Provides larger business/product context. Mentors on specific tech stacks/technologies

Qualifications and Education Requirements:

• Minimum 4-6 years of related experience as a full stack developer
• Expert in the field of Data Engineering/DW projects with Google Cloud based Data Engineering solutions
• Designing and developing enterprise data solutions on GCP cloud platform with native or third-party data technologies.
• Good working experience with relational databases and NoSQL databases including but not limited to Oracle, Spanner, BigQuery etc.
• Expert level SQL skills for data manipulation (DML), data validation and data manipulation
• Experience in design and development of data modeling, data design, data warehouses, data lakes and analytics platforms on GCP
• Expertise in designing ETL data pipelines and data processing architectures for Datawarehouse
• Experience in technical design and building both Streaming and batch processing systems
• Good experience in Datawarehouse in designing Star & Snowflake Schemas and knowledge of Dimensional Data Modelling
• Work with data scientists, data team and engineering teams to use Google Cloud platform to analyze data, build data models on Big query, big table etc
• Working experience in Integrating different datasets from multiple data sources for data modelling for analytical and AI/ML models
• Take ownership of production deployment of code
• Understanding and experience in Pub/Sub, Kafka, Kubernetes, GCP, AWS, Hive, Docker
• Expertise in Java spring boot / Python or other programming languages used for Data Engineering and integration projects
• Strong problem-solving and analytical skills
• AI/ML exposure, MLOPS and Vertex AI is a great advantage
• Familiarity with DevOps practices like CICD pipeline
• Airline domain experience is a plus
• Excellent spoken and written communication skills
• GCP Cloud Data Engineer Professional is plus

We will give careful consideration to your application and review your details against the position criteria. You will receive separate notification as your application progresses.

Please note that only candidates who meet the minimum criteria for the role will proceed in the selection process.