Description

You will design, build, and maintain scalable data pipelines for real-time and batch analytics. You will own the cloud-native data infrastructure on Google Cloud Platform and enable trusted datasets for Tableau dashboards. You will also build AI/ML integrations to support predictive use cases.

Responsibilities

• Design and optimize ETL/ELT processes for structured and unstructured data from MongoDB, PostgreSQL, and APIs.
• Architect and manage data infrastructure within Google Cloud Platform, specifically BigQuery environments.
• Orchestrate data transformations using Cloud Composer and Airflow DAGs.
• Implement data monitoring, logging, and observability frameworks to ensure data quality and security.
• Build AI/ML models and integrations for predictive analytics, including lounge recommendations and capacity forecasting.

Required Skills

• 4-6 years of Data Engineering experience with proven hands-on work in Big Data technologies.
• Strong proficiency in Python and SQL for data ingestion, processing, and manipulation.
• Hands-on experience with GCP services: BigQuery, Dataflow, Cloud Storage, Pub/Sub, Cloud Composer, and Cloud Functions.
• Experience building data connectors with relational and non-relational databases (MongoDB, PostgreSQL) and custom APIs.
• Experience with CI/CD practices using Git and Jenkins.
• Understanding of data modeling principles, ETL/ELT processes, and data warehousing concepts.
• Experience with statistical/predictive modeling, machine learning, and A/B testing.
• Experience supporting AI integrations and ML pipelines, including BigQuery ML or other GCP AI/ML services.
• Experience working with BI tools including Tableau and PowerBI.

Preferred Skills

• Experience with LLMs, Generative AI, or NLP systems.
• Familiarity with feature stores, model registries, and data governance standards.
• Experience with real-time analytics and streaming architectures.

Key Skills

Education

Bachelor's degree