Data Platform Engineer

Location: Gahanna, OH (Hybrid)

Duration: 12 Month Contract

Position Summary:

The Solution Engineer is responsible for designing, building, integrating, and supporting the enterprise Unstructured Data Platform. This role serves as a technical leader within a single-stack platform organization and focuses on enabling business capabilities through scalable cloud-native solutions, reusable ingestion services, metadata management, AI-enablement, and operational excellence.

The Solution Engineer will collaborate with Product Owners, Data Engineers, Platform Engineers, Data Scientists, and business stakeholders to deliver solutions that support ingestion, storage, governance, annotation, analytics, and AI-driven use cases.

This role supports the long-term vision of establishing a reusable enterprise platform that can manage and operationalize unstructured data including imagery, documents, LiDAR, sensor data, video, inspection records, and AI-generated metadata.

Primary Responsibilities:

Platform Architecture & Solution Design

• Design scalable cloud-native solutions supporting enterprise unstructured data workloads.
• Define reference architectures, patterns, and standards for platform capabilities.
• Develop technology roadmaps aligned to business and platform strategy.
• Ensure solutions meet security, reliability, scalability, and operational requirements.
• Translate business requirements into technical solution designs.
• Data Ingestion & Integratio

Platform & Cloud Engineering

• * Build and support cloud-based platform services.
• * Implement Infrastructure-as-Code (IaC) practices.
• * Develop automation for deployment, provisioning, and platform operations.
• * Support monitoring, observability, operational health, and performance optimization.
• * Participate in platform support and incident response activities.

Metadata & Governance Enablement

• Design metadata structures and data discovery capabilities.

Support implementation of:

• Metadata catalogs
• Data lineage
• Search and discovery
• Data classification
• Retention policies
• Partner with governance and security teams to ensure compliance requirements are met.

Annotation & AI Enablement

• Integrate annotation and human-review services into platform workflows.
• Support AI/ML lifecycle activities including:
• Ground-truth data management
• Defect taxonomy management
• AI feedback capture

Model output integration

• Enable AI metadata storage and retrieval patterns.

Human-in-the-Loop Workflows

• Design workflows that combine automation and human review.
• Support implementation of inspection and validation processes.
• Enable business users to review, correct, and enrich AI-generated results.
• Ensure traceability and auditability of user actions.

DevSecOps & Automation

• Implement CI/CD pipelines and deployment automation.
• Apply security controls throughout the platform lifecycle.
• Automate testing, monitoring, and operational processes.
• Support resiliency, backup, recovery, and operational readiness activities.

Required Qualifications

Education

Bachelor's degree in:

• Computer Science
• Engineering
• Information Systems
• Related technical discipline

Technical Experience

• * 5+ years of solution engineering, software engineering, platform engineering, or cloud engineering experience.
• * Experience designing distributed cloud-native architectures.
• * Experience with API design and system integrations.
• * Experience working with enterprise data platforms.
• * Experience implementing automation and DevOps practices.
• * Experience translating business requirements into technical solutions.
• Cloud & Platform Experience

Experience with one or more:

• * AWS
• * Azure
• Google Cloud Platform

Experience with:

• Object storage platforms
• Data ingestion frameworks
• Event-driven architectures
• Modern API technologies
• CI/CD tooling