Cloud Engineer

Cloud Data Engineer 

Location:  Fayetteville, AR
Onsite: Yes
Schedule:  M-F, 8-5 (flexible)
Type:  Direct Hire, Permanent
Salary:  $130,000 - $165,000

Overview

Our organization spans several industries—including automotive retail, heavy equipment, beverage distribution, and aviation—and has been privately operated for decades. As we continue expanding through acquisitions, we are modernizing our data ecosystem on Google Cloud to support enterprise-wide analytics, operational insights, and emerging AI workloads.

We are hiring a Cloud Data Engineer to help establish a new data architecture from the ground up. This is a net-new engineering role focused on designing and delivering a contemporary data platform rather than supporting legacy systems.

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Key Responsibilities

<>Platform Architecture & Development

• Architect and deploy a multi-layered data environment (bronze/silver/gold) in BigQuery, including ingestion, transformation, and semantic modeling.
• Configure Dataplex to serve as the central framework for cataloging, lineage tracking, governance, and data quality across business domains.
• Build ingestion pipelines—batch and real-time—from diverse sources such as dealer management systems, ERP tools, IoT and telematics feeds, SaaS providers, and on-prem databases using technologies like Dataflow, Pub/Sub, Datastream, Cloud Composer, and Cloud Run.
• Develop modular SQL and transformation workflows using dbt or Dataform with robust testing, documentation, and version control practices.

<>Operations, Reliability & Security

• Use infrastructure-as-code to provision cloud assets and implement CI/CD automation for both data workflows and platform components.
• Create and maintain clear environment boundaries (Dev / Test / Prod) while ensuring consistent deployment patterns.
• Establish monitoring, alerting, and cost-optimization practices to manage BigQuery compute allocation, storage optimization, and pipeline performance.
• Apply security best practices including IAM policy design, VPC Service Controls, customer-managed encryption keys, and fine-grained access controls.
• Contribute to data protection initiatives such as DLP, masking frameworks, and classification schemes to support analytical and AI-driven workloads.

<>Business Enablement & Data Products

• Collaborate with leaders across multiple verticals to interpret business requirements and translate them into reliable, scalable data assets.
• Deliver curated data models and subject-area marts optimized for BI platforms like Looker, Power BI, or Tableau.
• Prepare the platform for advanced AI/ML scenarios—feature engineering pipelines, vector stores, Vertex AI integrations, and RAG-oriented architectures.
• Produce technical documentation including architectural diagrams, data contracts, and operational runbooks.

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Qualifications

• 5+ years of hands-on experience in data engineering, cloud engineering, or platform-focused development (additional requirements can be added as needed).

TULIT