Data Architect

Immediate need for a talented Data Architect. This is a 12+months contract opportunity with long-term potential and is located in Columbus, IN(Onsite). Please review the job description below and contact me ASAP if you are interested.
Job ID:26-33600
Pay Range: $65 - $70/hour.  Employee benefits include, but are not limited to, health insurance (medical, dental, vision), 401(k) plan, and paid sick leave (depending on work location).
Key Responsibilities:

• Work Focus:
• 70%: Data Architecture, AI Governance, AI Agents, and Computer Vision
• 30%: DevOps, SecOps, and production deployment
• Data Architecture and Governance — 35%
• Define and implement enterprise data integration and storage strategies.
• Design scalable architectures for databases, data lakes, APIs, and analytics platforms.
• Develop physical, logical, and metadata models.
• Establish data quality, accuracy, ownership, lineage, retention, and access-control standards.
• Define governance metrics and monitor alignment with enterprise data strategies.
• Lead data migration, transformation, validation, and modernization activities.
• Align solution architecture with central enterprise architecture standards.
• Design and implement microservices and reusable data services.
• Monitor and optimize database performance, scalability, availability, and cost.
• Support analytics, reporting, and data-lake integration.
• AI Governance, AI Agents, and Knowledge Solutions — 25%
• Develop a strategy for making trusted enterprise data available to AI applications and agents.
• Define AI governance standards covering security, privacy, traceability, model risk, human oversight, and responsible AI.
• Identify and prioritize knowledge-based AI and agentic AI use cases.
• Design knowledge repositories, semantic search, vector databases, and retrieval-augmented generation solutions.
• Develop AI solutions from proof of concept through production readiness.
• Create reusable frameworks for subject-matter-expert agents and enterprise knowledge assistants.
• Establish long-term support, ownership, lifecycle, and sustainability plans for AI solutions.
• Define AI performance, accuracy, adoption, cost, and business-value metrics.
• Implement monitoring for model quality, data drift, hallucination risk, and solution reliability.
• Computer Vision — 10%
• Design and implement computer vision solutions for image and video analysis.
• Develop pipelines for image ingestion, annotation, preprocessing, model training, inference, and monitoring.
• Support use cases such as object detection, classification, OCR, defect identification, visual inspection, and document-image processing.
• Evaluate computer vision models and services based on accuracy, latency, scalability, explainability, and cost.
• Establish governance standards for image data, labeling quality, model validation, privacy, and retention.
• Deploy computer vision solutions using cloud, edge, or hybrid architectures.
• Transition computer vision prototypes into reliable production applications.
• DevOps and SecOps — 30%
• Establish software development, coding, documentation, testing, and code-review standards.
• Design and optimize CI/CD and DevSecOps pipelines.
• Automate application, infrastructure, database, and AI-model deployments.
• Integrate static code analysis, dependency scanning, container scanning, secret detection, and vulnerability management.
• Define encryption, identity, access-control, auditing, logging, and sensitive-data handling requirements.
• Ensure compliance with enterprise cybersecurity and regulatory requirements.
• Support containerized and microservices-based deployments.
• Implement monitoring, alerting, incident response, backup, recovery, and operational-support processes.
• Troubleshoot production issues and drive root-cause analysis and corrective actions.
• Develop implementation roadmaps in coordination with technical and business leadership.

Key Requirements and Technology Experience:

• Bachelor’s degree in Computer Science, Data Science, Software Engineering, Information Systems, Electrical Engineering, or a related technical field.
• Seven or more years of experience in data engineering, software development, cloud architecture, AI/ML, or related areas.
• Three or more years of experience designing enterprise data or solution architectures.
• Hands-on experience with AWS cloud services and cloud-native solution development.
• Strong experience with relational databases, NoSQL databases, data lakes, and data warehouses.
• Experience developing data integration pipelines using ETL/ELT, APIs, messaging, or event-driven architectures.
• Strong knowledge of data modeling, metadata management, data lineage, data quality, and governance.
• Experience developing or deploying AI, machine learning, generative AI, or knowledge-based solutions.
• Working knowledge of computer vision concepts and image-processing workflows.
• Experience implementing CI/CD pipelines and DevSecOps controls.
• Strong understanding of encryption, identity management, access controls, audit logging, and secure handling of sensitive data.
• Proficiency in Python and SQL.
• Experience with Git-based development, automated testing, and code-review practices.
• Ability to translate business requirements into scalable technical solutions.
• Strong communication skills with the ability to work across architecture, cybersecurity, engineering, IT, and business teams.
• Cloud: AWS, including services for compute, storage, databases, security, monitoring, and AI/ML
• Programming: Python, SQL, scripting, and API development
• Data Platforms: Relational databases, NoSQL, data lakes, data warehouses, and vector databases
• Data Integration: ETL/ELT, REST APIs, event streaming, messaging, and microservices
• AI: Generative AI, AI agents, RAG, prompt orchestration, embeddings, model evaluation, and responsible AI controls
• Computer Vision: OpenCV, image preprocessing, classification, object detection, OCR, model evaluation, and inference pipelines
• DevOps: Git, automated testing, CI/CD, infrastructure as code, release management, and environment management
• Containers: Docker and Kubernetes or equivalent container platforms
• Security: Secure coding, vulnerability scanning, secrets management, IAM, encryption, audit logging, and compliance
• Monitoring: Application, database, pipeline, infrastructure, and AI-model observability

Our client is a leading IT Industry, and we are currently interviewing to fill this and other similar contract positions. If you are interested in this position, please apply online for immediate consideration.
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