Description

KEY RESPONSIBILITIES

•    Design and build scalable ETL/ELT pipelines using Apache Airflow, Apache Spark, and GCP Dataflow

•    Develop and maintain BigQuery data models, schemas, and performance-optimized SQL queries

•    Build and maintain data pipelines feeding AI/ML feature stores and forecasting models

•    Collaborate with AI Developers to ensure high-quality, low-latency data access for model training

•    Manage and optimize Cloud Composer DAGs and pipeline orchestration

•    Implement data quality monitoring, alerting, and lineage tracking

•    Participate in data platform architecture decisions and documentation

REQUIRED QUALIFICATIONS

•    3+ years (Intermediate) or 5+ years (Specialist) of data engineering experience

•    Hands-on experience with Apache Airflow for pipeline orchestration

•    Proficiency in Apache Spark for large-scale data processing

•    Strong SQL skills including complex query optimization and BigQuery-specific capabilities

•    Experience with GCP data services: BigQuery, Cloud Storage, Pub/Sub, Dataflow

•    Solid understanding of ETL/ELT patterns and data warehousing principles

PREFERRED QUALIFICATIONS

•    GCP Professional Data Engineer certification

•    Experience supporting ML/AI data infrastructure (feature engineering, training datasets)

•    Familiarity with real-time streaming (Kafka, Dataflow/Flink)

•    Retail or large-scale consumer data experience

Key Skills

Education

Bachelor's degree