Data Engineer

Overview

Hybrid
Depends on Experience
Contract - W2
Contract - 12 Month(s)

Skills

Analytics
Apache Airflow
Apache Kafka
Apache Spark
Business Intelligence
Data Processing
Data Storage
Database
Data Engineering
Data Flow
Dashboard
Google Cloud Platform
Machine Learning (ML)
Kubernetes
Python
SQL
Vertex
Terraform
Scala
Java
Jenkins

Job Details

Job Description: Data Engineer Location: Phoenix, AZ (Day 1 Onsite Hybrid: 3 days in office, 2 days WFH) Employment Type: Long-Term Contract
Experience Required: 12+ years

Position Overview

We are looking for a Data Engineer with deep expertise in Google Cloud Platform (Google Cloud Platform) to design, build, and optimize scalable data solutions. The ideal candidate will have hands-on experience with Google Cloud Platform services (Cloud Functions, GKE, BigQuery, Cloud SQL, IAM, Looker, GCS, Firebase) and hold a Google Cloud Platform certification (Professional Data Engineer or Cloud Engineer).

Key Responsibilities

  • Design, develop, and deploy data pipelines and cloud-native applications using Google Cloud Platform services (BigQuery, Cloud Functions, Dataflow, Pub/Sub, etc.).
  • Manage and optimize GKE (Google Kubernetes Engine) for containerized data workloads.
  • Implement data storage solutions using Cloud SQL, BigQuery, Firestore, and Google Cloud Storage (GCS).
  • Configure IAM policies, security controls, and access management in Google Cloud Platform.
  • Develop dashboards and analytics using Looker for business intelligence.
  • Automate workflows using Cloud Composer (Apache Airflow) and CI/CD pipelines (Cloud Build, Jenkins).
  • Collaborate with cross-functional teams to ensure scalable, secure, and high-performance data architectures.
  • Troubleshoot and optimize Google Cloud Platform services for cost, performance, and reliability.
  • Mentor junior engineers and lead best practices in Google Cloud Platform data engineering.

Required Skills & Experience

  • 12+ years in IT, with 5+ years of hands-on Google Cloud Platform experience.
  • Must be Google Cloud Platform certified (Professional Data Engineer or Cloud Engineer).
  • Strong expertise in Google Cloud Platform services:
    • Data & Analytics: BigQuery, Dataflow, Dataproc, Pub/Sub
    • Compute & Containers: Cloud Functions, GKE, App Engine
    • Storage & Databases: Cloud SQL, Firestore, GCS
    • Security & IAM: Identity & Access Management, VPC, Data Encryption
    • BI & Visualization: Looker, Data Studio
  • Proficiency in Python, Java, or Scala for data processing.
  • Experience with real-time streaming (Pub/Sub, Apache Kafka) and batch processing (Dataflow, Spark).
  • Knowledge of Infrastructure as Code (Terraform, Deployment Manager).
  • Strong understanding of DevOps practices (CI/CD, GitOps, Monitoring/Logging).

Preferred Qualifications

  • Experience with Firebase (Firestore, Realtime DB, Auth).
  • Knowledge of machine learning pipelines (Vertex AI, AutoML).
  • Familiarity with multi-cloud or hybrid cloud architectures.
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