GCP Data Engineer

Intone Inc; Phoenix, Northern (AZ, KY); Hybrid; USD 120,000 - 170,000; Full time

Job summary

Intone Networks Inc. seeks a GCP Data Engineer for a 6+ month contract in Phoenix, AZ. You will design scalable data solutions, implement governance, and ensure reliability across enterprise pipelines.

You will build ETL/ELT pipelines with Python and Spark, establish data quality rules, lineage, and access controls, and collaborate with stakeholders to enable observability and trust in data assets.

Qualifications

• Bachelor's or Master's degree in CS, Engineering, or related field.
• Strong Python and Spark experience.
• Proven track record building reliable ETL/ELT pipelines in production.
• Hands-on data quality frameworks experience.
• Experience implementing data governance (cataloging, lineage, metadata, access controls).
• Familiarity with cloud data platforms such as AWS, Azure, or GCP.
• Strong understanding of data modeling and schema evolution.

Responsibilities

• Design and build scalable data pipelines using Spark and Python.
• Establish governance frameworks with data quality rules, lineage, and access controls.
• Implement data reliability practices with validation checks and alerts.
• Develop automated workflows with Airflow.
• Collaborate with stakeholders to define data contracts and standards.
• Enable end-to-end observability of pipelines and data freshness.
• Document data assets, lineage, and governance policies.
• Preferred: support ML pipelines with feature engineering and validation.

Skills

Python

Apache Spark

Data governance

ETL/ELT pipelines

Data quality frameworks

Metadata management

Access controls

Data modeling

Schema evolution

Observability

Education

Bachelor's or Master's degree in Computer Science, Engineering, or related field

Tools

Airflow

GCP

Job description

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
  • 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