84.51°
Data Architect (P4642)
Cincinnati, OH; Chicago, IL
Sponsorship not specifiedDetected 1 day ago
PythonSQLSnowflakeDatabricksAzureCloud PlatformsDatadogMachine LearningdbtData EngineeringData ScienceAgentic AIMLOpsLeadershipCommunicationCollaborationProblem Solving
About the role
- The Data Architect plays a key role within our Software Architecture group by leading the design and delivery of modern software solutions that support our commercial products and platforms.
Responsibilities
- Design enterprise data architectures for the KPM portfolio, including data modeling, integration patterns, pipeline design, and cloud-native storage strategies that are understandable to both technical and non-technical audiences.
- Architect AI-ready data platforms that support both transactional and analytical workloads, with an emphasis on data product design, conformed dimensions, and patterns that accelerate AI and ML development (feature engineering, model training, and inference serving).
- Guide technical decision-making with engineering and data science teams on architectural trade-offs: build vs. buy, technology selection, data model design, and platform evolution.
- Develop reference architectures and reference implementations, including rapid prototypes, that establish consistent patterns across data engineering, ML pipelines, and AI systems.
- Implement and evolve data governance frameworks, applying established organizational standards to AI systems, including model access control patterns, cost attribution strategies, data lineage, and guardrails that ensure AI systems are secure, compliant, and auditable within the enterprise data perimeter.
- Partner with Data Scientists, ML Engineers, Product Managers, and Engineering teams to ensure the data platform strategy delivers against requirements, scope, and timelines.
- Mentor data engineering and AI platform teams on architectural thinking, data modeling principles, and best practices for building production-grade data systems.
- Ensure security and compliance by partnering with security teams to validate that proposed architectures adhere to enterprise best practices and data governance requirements.
- Demonstrated ability to design semantic layers and data abstraction patterns that serve both analytical and AI/ML consumers.
- Experience architecting AI-ready data platforms, including data product design, conformed dimensions, and patterns that support feature engineering, model training, and agentic AI workflows.
Requirements
- Bachelor's Degree or higher in a field related to software development, technology, or engineering or a related field required.
- 7+ years of experience in engineering organizations, with at least 4+ years in a data architecture or technical leadership role.
- Experience with monitoring and observability patterns for data platforms (Datadog or equivalent).
- Experience with cloud cost management for data platforms, including usage monitoring, cost attribution, and spend projection across Databricks and Snowflake environments.
- Strong understanding of cloud-native data platforms and services, including Azure Data Lake Storage, Databricks Workflows, Delta Lake, and Azure cloud services broadly.
- Proficiency in SQL and at least one data engineering language (Python strongly preferred).
Skills
- Strong problem-solving skills with a proactive approach to technical challenges.
- Experience transitioning systems from legacy batch architectures to event-driven or streaming patterns.
- Ability to influence and guide technical teams through expertise and collaborative leadership.
- Comfort making time-sensitive architectural decisions with incomplete information.
- Experience with managed AI platforms operating within an enterprise data perimeter (e.g., Snowflake Cortex AI, Azure OpenAI Service).
- Familiarity with modern MLOps practices and tools (MLflow, model registries, feature stores).
- Experience designing semantic layers using tooling such as dbt Semantic Layer, Cube, or equivalent.
- Ad server or retail media technology data modeling experience.
- Event-driven architecture experience.
- Business Acumen, Communication and Leadership:
- Strong business sense with the ability to translate business requirements into scalable technical solutions.
- Excellent communication
Compensation
- The stated salary range represents the entire span applicable across all geographic markets from lowest to highest.
Benefits
- Direct experience with Databricks OR Snowflake (expertise in one is required; both is a bonus).
This listing is sourced directly from 84.51°'s careers page and normalized into a canonical job model.