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Tier-1 brand, mid-level generalist data role in metro with broad Spark/SQL/Airflow skills increases competition.
Core data engineering skills are highly transferable across industries.
Explicit 5+ years plus mandatory Spark, SQL, Airflow and platform experience increases screening strictness.
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Design, build, optimize, and operate scalable batch data pipelines with Apache Spark and orchestration tools like Airflow across large distributed data platforms.
Develop and maintain analytics-ready data models (fact tables, dimensions, aggregates) powering BI dashboards, experimentation, and executive reporting at Expedia Group scale.
Contribute to platform capabilities for metric computation, AI-assisted workflows, data access services, and data quality/observability to improve reliability and scalable metric consumption.
5+ years of data engineering experience building production-grade data solutions at scale.
Strong proficiency in SQL (complex joins, window functions, query tuning) and hands-on experience with Apache Spark including tuning and troubleshooting workloads.
Experience with big data and lakehouse technologies such as Trino/Presto, Iceberg or Delta Lake, and workflow orchestration tools like Airflow.
Work Experience Required: 5+ years in relevant data engineering roles. Notice period: Not explicitly mentioned in the JD.
Experienced in large-scale batch data pipeline development and operational support using Spark and Airflow in complex distributed environments.
Skilled in creating and optimizing semantic layers, metric stores, and governed analytic platforms supporting executive reporting and self-serve analytics.
Demonstrates strong ownership on medium-to-large end-to-end deliverables and collaborates effectively across cross-functional teams including analysts, data scientists, and product managers.