We are seeking a GCP Data Engineer for a contract position in Phoenix, Arizona, with a duration of 6 months or longer. In this role, you will design and implement scalable data solutions, establish governance frameworks, and ensure data reliability across enterprise pipelines.
Responsibilities
Design and build scalable, fault-tolerant data pipelines using Apache Spark and Python
Establish and enforce data governance frameworks, including data quality rules, lineage, cataloging, and access controls
Implement data reliability practices such as validation checks, anomaly detection, SLAs/SLOs, and automated alerting
Develop and maintain automated data workflows using orchestration tools such as Airflow
Partner with stakeholders to define data contracts, schemas, and standards across domains
Enable end-to-end observability of data pipelines, including freshness, completeness, and accuracy
Document data assets, lineage, and governance policies to improve discoverability and trust
Preferred: Support machine learning pipelines, including feature engineering, training data validation, and monitoring model input/output data quality
Qualifications
Required
Bachelor's or Master's degree in Computer Science, Engineering, or related field
Strong programming skills in Python and experience with Apache Spark
Proven experience building reliable ETL/ELT pipelines in production environments
Hands-on experience with data quality frameworks
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Experience implementing data governance principles including cataloging, lineage, metadata management, and access control
Familiarity with cloud data platforms such as AWS, Azure, or GCP
Strong understanding of data modeling, schema evolution, and data lifecycle management
Preferred
Experience supporting ML pipelines with a focus on data validation and feature stores