Data Architect

Data Architect - Contract to Hire, Omaha/Remote

• 5+ years of experience in leading data architecture initiatives, including cloud-native data platforms, machine learning lifecycle management, and enterprise data integration.
• Expertise in distributed data systems, data warehouse, data lakehouse architecture, and model operationalization frameworks such as MLflow, Sagemaker, or similar.
• Proficiency in Python, SQL, Snowflake and Mongo
  
  DB and cloud technologies (AWS preferred), with experience deploying ML models using containers, APIs, or serverless frameworks.
• Proficiency in logical and physical data modeling, multidimensional modeling, normalization and denormalization techniques.
• Experience in building data systems in microservice environments that provide access to data for operational and analytical needs (BI/ML/AI).
• Experience translating business strategies into data solutions with measurable outcomes.
• Proficiency in design and development of ETL/ELT methodologies from source to target supporting data processing and transformations to deliver data-driven business insights and decisions.
• Strong understanding of data governance, explainability, and responsible data principles.
• Familiarity with data observability tools, CI/CD for ML, and lineage/trust frameworks.
• Comfortable working in agile environments and guiding architecture for Agile Release Trains (ART).
• Excellent communication, stakeholder engagement, and cross-functional leadership skills.
• TOGAF Certified.
• Group Benefits or insurance industry experience.
• Experience with Mongo
  
  DB, Snowflake, AWS AI/ML stack (Sage Maker, Glue, Redshift, Bedrock, etc.).
• Familiarity with MLOps, data mesh principles, and real-time analytics (Kafka, Spark).
• Artificial Intelligence experience is preferred but not required. A strong willingness to learn and grow in AI technologies is highly valued

Client is seeking a visionary Data Architect to lead the design and evolution of intelligent data-driven platforms across our Workplace Solutions division. This position will champion strategic initiatives leveraging data, analytics, and artificial intelligence to enhance customer experiences, optimize operations, and drive business value through scalable and ethical technology solutions.

This role is essential in shaping our data architecture, artificial intelligence strategy, and governance models, enabling intelligent automation, machine learning operations (MLOps), and integrated insights. The ideal candidate brings deep technical expertise and an innovative mindset to accelerate our journey toward becoming a data-powered organization.

As a Lead Architect, you will work closely with business and technology partners to deliver modern, secure, and adaptive data ecosystems and AI solutions. You will contribute to our transformation by establishing a future‑ready data foundation and operationalizing AI to unlock actionable intelligence.

• Data and AI Architecture Leadership:
  Design and implement advanced data platforms and AI architecture, enabling enterprise‑scale analytics, machine learning, and intelligent automation across the division.
• Strategy & Planning:
  Collaborate with enterprise architects and business stakeholders to define a vision and roadmap for data modernization, MLOps, and AI governance aligned to strategic outcomes.
• AI Innovation & Prototyping:
  Lead the development of AI models, POCs, and pipelines using cutting‑edge technologies. Explore "what‑if" scenarios, whiteboarding, and design sprints to evaluate new opportunities and validate business impact.
• Governance & Ethics:
  Establish and uphold standards for data quality, stewardship, ethical AI practices, and secure model deployment while promoting regulatory compliance and trust.
• Mentorship & Enablement:
  Coach engineers and analysts in data modeling, feature engineering, and ML development. Promote knowledge sharing and establish best practices across data science and data engineering teams.
• Collaboration & Integration:
  Integrate data solutions with microservices, event‑based architectures, and external business partners, ensuring scalability, observability, and operational readiness.