Data Architect

Overview

About LSB LSB is committed to playing a leadership role in the production of low and no carbon products that build, feed and power the world. The LSB team is dedicated to building a culture of excellence in customer experiences as we deliver essential products across the agricultural and industrial end markets and, in the future, the energy markets. Join our team and help us develop innovative solutions that will improve the quality of life for current and future generations.

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Data Architect is a senior technical leader responsible for the design, evolution, and reliability of the enterprise data platform. This role owns platform architecture across cloud environments and ensures data systems are scalable, secure, and optimized for analytics and reporting. The Data Architect sets technical direction, establishes standards, and partners across teams to enable trusted data delivery from cloud data platforms to data visualization/analysis environments and tools.

Location: This role is based out of Oklahoma City, OK and will utilize a hybrid schedule (3 days in-office, 2 days remote).

• Data Platform Architecture & Ownership:
  Design and evolve a cloud-based data platform leveraging best of breed tools and expertise of said platform.
• Own the architecture and operational health of the cloud data platform.
• Define platform standards for data ingestion, transformation, storage, and consumption.
• Make architectural decisions that balance scalability, performance, cost, and maintainability.

• Cloud & Infrastructure Leadership:
  Lead design and implementation of cloud-native data solutions using best of breed tools and processes.
• Partner with infrastructure and security teams on networking, identity, encryption, and governance.
• Drive infrastructure-as-code, automation, and platform reliability practices.

• Snowflake & Analytics Enablement:
  Architect and optimize cloud data platform schemas, data models, and performance strategies.
• Establish best practices for workload management, cost optimization, and data access.
• Enable analytics and reporting use cases through well-modeled, reliable data structures.

• Power BI & Data Consumption:
  Partner with BI and analytics teams to deliver semantic models and trusted, governed and reliable datasets.
• Ensure data models are optimized for reporting performance and usability.
• Promote data discoverability, documentation, and self-service analytics.

• Technical Leadership & Standards:
  Serve as a technical authority and escalation point for complex data platform issues.
• Lead design reviews and influence data engineering practices across teams.
• Mentor data engineers and guide platform-aligned solution design.

• Operational Excellence:
  Define and implement monitoring, alerting, and data quality practices.
• Lead incident response and root cause analysis for data platform issues.
• Improve CI/CD pipelines, deployment automation, and platform observability.