Data & AI Engineer

Data & AI Engineer
• 4-6 years of Data Engineering experience with proven hands-on experience in Big Data technologies and Business Intelligence tools.
• Understanding of Agile or other rapid application development methods. Exposure to design and coding across one or more platforms and languages as appropriate.
• Exposure to application design, software development, and automated testing methodologies.
• Experience with CI/CD practices using Git, Jenkins, and code integration/review processes.
• Backend platform: Experience building data connectors with relational & nonrelational backend databases including MongoDB, PostgreSQL, and custom API Connectors.
• Google Cloud Platform Expertise: Hands-on experience with GCP services like BigQuery, Dataflow, Cloud Storage, Pub/Sub, Cloud Composer (Airflow DAGs), and Cloud Functions.
• Programming Languages: Strong proficiency in Python and SQL for data ingestion, processing, and manipulation.
• ETL/ELT: Experience with ETL/ELT processes and data warehousing concepts.
• Data Modeling: Understanding of data modeling principles and techniques.
• Cloud Technologies: Knowledge of cloud computing concepts and standard processes.
• AI / ML: Experience with Statistical / Predictive Modeling, Machine Learning, A/B testing, and designing feature experiments
• AI Frameworks: • Experience supporting AI integrations ML pipelines including BigQuery ML, or other GCP AI/ML services
• BI Tools: Experience working with BI tools including Tableau and PowerBI
• Problem-Solving: Excellent analytical and problem-solving skills.
• Experience working with large datasets, ODL, identifying ingestion issues and proactively collaborating to resolve data related issues.
• Passion for travel/airports a plus.
• Experience with LLMs, Generative AI, or NLP systems.
• Familiarity with feature stores and model registries.
• Knowledge of data governance and compliance standards.
• Experience with real-time analytics and streaming architectures.
• Certifications in cloud or AI technologies.
• Design, build, and maintain scalable data pipelines (batch and streaming) supporting real-time / near-real-time data integration for Lounge Services Analytics use cases.
• Develop and optimize ETL/ELT processes for structured and unstructured data from various backend DBs and sources including MongoDB, PostgreSQL, APIs, and third-party systems.
• Architect and manage cloud-native data infrastructure/warehouses within Google Cloud Platform (BigQuery) environments.
• Orchestrate Data Transformations with Cloud Composer / Airflow DAGs.
• Enable trusted, analytics-ready datasets to support Tableau dashboards and analytics.
• Experience with observability and monitoring tools such as Datadog, CloudWatch, Prometheus, or similar platforms.
• Implement data monitoring, logging, and observability frameworks to ensure data quality, integrity, governance and security standards are met.
• Build AI / ML models and integrations to support predictive & personalized use cases including lounge recommendations, capacity forecasting, and lounge optimization
• Collaborate with cross-functional teams including Analytics, Product & Business to define data requirements and deliver solutions.
• Optimize data storage and processing for performance and cost-efficiency (partitioning and indexing solutions).
• Implement and enforce data governance standards, including data classification, access controls, and retention policies.
• Develop and maintain metadata management practices, including data lineage, catalog documentation, and business glossary alignment.

Salary Range- $100,000-$120,000 a year