Role Overview
You will design, build, and maintain scalable data pipelines and infrastructure to support analytics and machine learning initiatives. You will work closely with data scientists, analysts, and business stakeholders to ensure high-quality, accessible data across the organization.
Key Responsibilities
- Develop and maintain robust ETL/ELT pipelines for ingesting and transforming flight, passenger, and operational data.
- Design and implement data models and architectures optimized for performance and scalability using Object oriented programming.
- Collaborate with cross-functional teams to understand data requirements and deliver solutions.
- Ensure data quality, integrity, and security across all systems.
- Monitor and optimize data workflows for real-time and batch processing.
- Support the deployment of machine learning models into production environments using Object-Oriented Programming (OOP) principles for modularity, scalability, and maintainability.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
- 2+ years of experience in data engineering or related roles.
- Hands-on experience with Google Cloud Platform (GCP) is a must.
- Experience with Databricks and BigQuery.
- Proficiency with Git for version control.
- Proficiency in SQL and Python; experience with Spark, Airflow, or similar tools.
- Familiarity with data warehousing solutions (e.g., Snowflake,Redshift).
- Strong understanding of data modeling, data lakes, and distributed systems.
Preferred Skills
- Experience in the aviation or travel industry.
- Knowledge of real-time data processing (pub-sub).
- Exposure to machine learning workflows and MLOps.
