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# GCP Data Engineer

- **Company:** Stefanini
- **Location:** Dearborn, MI, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Elastic Compute Cloud, Applications Architecture, Big Data, BigTable, BigQuery, Cloud Computing, Cloud Engineering, Cloud Storage, Continuous Integration, Extract Transform Load (ETL), Data Warehousing, Expert Systems, Data Flow Control, Identity and Access Management, Mobile Application Software, Java Virtual Machine (JVM), Python (Programming Language), PostgreSQL, Machine Learning, OAuth, Redis, Rule Engine, Systems Integration, Management of Software Versions, Google Cloud, Cloud Platform System, Snowflake, Database Optimization, Apache Spark, Spring-boot, Backend, Kotlin, Kubernetes, Star Schema, Apache Kafka, Data Management, Machine Learning Operations, Restful APIs, Grpc, Data Pipelines, Docker, Microservices
- **Published:** September 23, 2026
- **Apply:** https://www.thejobnetwork.com/job/5c8becfc-cb86-4b56-be6c-4505c6484fa8/gcp-data-engineer

## About the Role

GCP, Big Data, BigQuery, Artificial Intelligence & Expert Systems, API

Skills Preferred

 * Google Cloud Platform
 * Familiarity with advanced GCP services beyond core compute and storage, such as Vertex AI, Dataflow, Cloud Composer / Airflow, BigQuery ML
 * Using Cloud Composer to orchestrate scheduled data pipelines that feed into a BigQuery data warehouse.
Experience Required
7+ years of experience in IT, 5+ years of experience in software developmentGoogle Cloud Platform (GCP)Experience deploying and managing services on Google Cloud Platform, including Compute Engine, Cloud Storage, IAM, and Cloud Functions.Example: Designing and implementing a cloud-native application architecture using GKE with Cloud SQL and Pub/Sub.Big DataExperience working with large-scale data processing frameworks such as Apache Spark, Dataflow, or BigQuery.Example: Building ETL pipelines that process terabytes of daily event data and transform it for downstream analytics.Data WarehousingExperience designing and maintaining data warehouse solutions such as BigQuery, Snowflake, or Redshift.Example: Modeling a star schema for a retail analytics platform that supports reporting on sales, inventory, and customer behavior.Artificial Intelligence and Expert SystemsExperience developing or integrating AI/ML models and rule-based expert systems.Example: Building a classification model
using Vertex AI to predict customer churn or implementing a rule engine that automates underwriting decisions.API DevelopmentExperience designing, building, and consuming RESTful or gRPC APIs.Example: Developing a versioned REST API with OAuth 2.0 authentication that serves as the integration layer between a mobile application and backend microservices.
Preferred Experience
Languages: Kotlin, Java, Python, or equivalent JVM/backend languageFrameworks: Spring Boot, gRPC, REST API designData Technologies: BigQuery, PostgreSQL, Redis, Bigtable, Kafka, or Pub/SubInfrastructure: GCP or equivalent, Docker, Kubernetes, CI/CD pipelinesPractices: TDD, MLOps-adjacent data pipeline patterns, database performance tuning, and API versioning, Bachelor's Degree, Certification Program

## Description

Design and develop scalable, high-performance backend services and APIs that process and expose telematics data, including:GPSTrip eventsDriver behaviorVehicle diagnosticsSensor telemetryBuild and maintain real-time and batch data pipelines that ingest high-volume vehicle event streams from messaging systems such as Pub/Sub and Kafka into data warehouses and operational stores.


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