Description

You will design, build, and maintain scalable data pipelines supporting real-time and near-real-time data integration for Lounge Services Analytics.

Responsibilities

• Develop and optimize ETL/ELT processes for structured and unstructured data from various sources, including MongoDB, PostgreSQL, and custom APIs.
• Architect and manage cloud-native data infrastructure and warehouses within Google Cloud Platform (BigQuery).
• Orchestrate data transformations using Cloud Composer / Airflow DAGs.
• Enable trusted, analytics-ready datasets to support Tableau dashboards and analytics.
• Implement data monitoring, logging, and observability frameworks to ensure data quality and security standards.

Required Skills

• 10+ years of Data Engineering experience with hands-on Big Data and BI tool exposure.
• Strong proficiency in Python and SQL for data ingestion, processing, and manipulation.
• Expertise with Google Cloud Platform (GCP), specifically BigQuery, Dataflow, Cloud Storage, Pub/Sub, and Cloud Composer.
• Experience building data connectors for relational (PostgreSQL) and non-relational (MongoDB) databases.
• Proven experience implementing CI/CD practices using Git and Jenkins.
• Solid understanding of ETL/ELT processes and data warehousing concepts.
• Familiarity with data modeling principles and cloud computing standard processes.
• Experience with automated testing and software development methodologies.

Key Skills

Education

Bachelor's degree