Hiring: Data Engineer - GCP Company: Core AI Consulting Inc Location: Phoenix, AZ Job Posted Time: 2026-09-16 14:53:10 Target Skills & Keywords : Agile, Airflow, Apache, Avro, BigQuery, CI/CD, Cloud Storage, Data Pipeline, Event-Driven, FastAPI, Flask, GCP, Git, GitHub Actions, IAM, Microservices, Parquet, Pub/Sub, PySpark, Python, REST, SQL, Snowflake, Spark, Terraform, dbt About the job Experience: •5+ years of experience designing and building scalable, production-grade data platforms. This role requires deep expertise in Google Cloud Platform, Python, PySpark, SQL, and distributed data processing across the complete data lifecycle—including ingestion, transformation, orchestration, storage, quality, and serving. •5+ years of hands-on experience in data engineering Required Skills: •Design, develop, and maintain enterprise-scale batch and streaming data pipelines using •Python, PySpark, Dataflow, Dataproc, Pub/Sub, BigQuery, and Cloud Composer •Build modular, reusable, and testable Python frameworks for data ingestion, transformation, validation, and pipeline automation •Develop high-performance data-processing solutions using •PySpark, Spark SQL, and Apache Beam •Integrate data from relational and NoSQL databases, REST APIs, flat files, cloud storage, third-party platforms, and event streams •Build real-time streaming pipelines using •, including windowing, triggers, watermarking, late-arriving data, deduplication, and delivery semantics Qualifications: •, including building production-grade data pipelines and platforms •Strong programming expertise in Python •, including object-oriented programming, reusable modules, exception handling, logging, testing, packaging, and performance optimization •Advanced experience with PySpark, Spark SQL, and Apache Spark •Strong knowledge of GCP data services •, particularly BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Composer, and Cloud Storage •Advanced SQL skills, including complex joins, window functions, CTEs, query optimization, and large-scale data transformation •, including schema design, partitioning, clustering, performance tuning, workload management, and cost optimization •Hands-on experience building batch and streaming pipelines with Dataflow and Apache Beam using Python •Strong experience designing and operating Spark workloads on Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!