As a champion of technical excellence, the Technical Analyst contributes to a culture of innovation, collaboration, and continuous improvement. You’ll work closely with architects, developers, and product teams to enhance operational efficiency, ensure platform stability, and explore emerging technologies—including AI and data-driven insights—that help keep our airline systems modern, scalable, and customer-focused.

Let your career take flight by joining a team that’s redefining the digital passenger experience at the forefront of global aviation.

Responsibilities:

Design & Implementation

• Manage implementation of solutions for exploratory data analysis and conducts implementation assessments based on Architecture Overview Documents (AOD) and Detailed Data Solutions.
• Provide accurate effort estimations and assess feasibility of proposed architectures and data models.

Pipeline Design & Development

• Design and develop cost-effective, scalable ELT pipelines using reusable components and frameworks.
• Document pipeline implementation approach including scheduling, dependencies, error handling, monitoring, and alerting.
• Monitor and resolve alerts/failures in prod/non-prod environments.
• Review and approve pipelines developed by data engineers.

Environment Setup & Collaboration

• Set up non-production and production environments including MFT flows, database/schema configurations, RBAC, cloud services, Git repositories, and defining appropriate branching strategies.
• Collaborate with stakeholders on UAT and production release strategies.

Technical Leadership & Mentorship

• Mentor and guide data engineers on best practices, business logic implementation, and quality assurance.
• Scramble and generate mock data for testing purposes.
• Identify and document technical debt; differentiate between defects and scope changes and effectively communicate with product team

DevOps & Data Modeling

• Lead deployment and transition-to-operations (TTO) activities for UAT and production.
• Apply strong understanding of DevOps processes, Star Schema, Data Vault, and data warehousing principles.

Qualifications

Professional Experience

• 3-5 years of experience leading enterprise data warehouse development teams.
• Proven success in Agile environments and cloud-based data platforms, especially Azure and Snowflake.

Technical Skills

• Expertise in building robust, scalable data pipelines for batch and streaming data.
• Proficiency in SQL, Python, stored procedures, and scheduling tools.
• Hands-on experience with ETL/ELT tools such as Azure Data Factory (ADF), Databricks, Snowflake, DBT and Talend.
• Skilled in implementing monitoring and alerting mechanisms for data pipelines.
• Strong capability in reviewing engineering deliverables for performance, scalability, and maintainability.
• Experience with prompt engineering and leveraging Generative AI (GenAI) to accelerate development and automate engineering workflows.

Education

• Bachelor’s degree in Engineering, Computer Science, Mathematics, or a related field.

Soft Skills

• Excellent communication, problem-solving, and analytical skills.
• Proven leadership and mentoring capabilities.
• Strong collaboration skills with cross-functional teams.
• Demonstrate punctuality and dependability to support overall team success in a fast-paced environment.