Principal Data and Analytics Engineer

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The Principal Data and Analytics Engineer holds comprehensive responsibility for the design, implementation, and continuous evolution of the organization's enterprise-wide data infrastructure and analytics capabilities.

This is an onsite position located in Springfield, MO.

• Help define and evolve enterprise data engineering blueprints, including data mesh, medallion architecture, and hybrid cloud data platforms.
• Set strategic direction for data platforms, tools, and services (e.g., Snowflake, GCP Big Query, dbt, Kafka, Airflow/Prefect) in alignment with future-state architecture and business priorities.
• Architect and design highly scalable, resilient, cost optimal and secure data platforms.
• Lead the design and implementation of next-generation data platforms, ensuring fault tolerance, high availability, and optimal performance for petabyte-scale data.
• Establish and enforce organization-wide best practices for data pipeline development, CI/CD for data workflows, automated deployment playbooks, and robust rollback strategies.
• Lead technology evaluation and adoption, proactively researching, evaluating, and championing the integration of cutting-edge data technologies, frameworks, and methodologies.
• Define and scale enterprise knowledge management frameworks that ensure consistent documentation, discoverability, and reusability of data assets across domains.
• Establish and govern standards for metadata management, data lineage, architectural diagrams, and runbooks.
• Lead the design of federated governance models that empower domain-aligned teams to operate autonomously while conforming to centralized policies, frameworks and playbooks.
• Collaborate with data governance, compliance, and security teams to operationalize policy-as-code frameworks for data retention, access control, and PII handling.
• Advocate for and enable self-service knowledge discovery through tightly integrated cataloging tools (e.g., Alation, Collibra) and automated documentation generators.
• Ensure robust documentation and versioning standards are embedded in CI/CD workflows for pipeline code, transformation logic, and schema changes.
• Architect implementation of scalable, automated data quality frameworks that evaluate data at rest and in motion spanning completeness, timeliness, consistency, accuracy, and integrity.
• Lead integration of data quality rules, metrics, and health indicators directly into orchestration layers (e.g., Prefect, Airflow) and transformation frameworks (e.g., dbt).
• Evangelize a culture of data trust and transparency by integrating data quality insights into user-facing dashboards, alerts, and product health reports.
• Identify and promote enterprise-wide data opportunities through thought leadership, white papers, reference architectures, and innovation labs.
• Act as technical advisor to senior executives on data modernization, AI readiness, and platform consolidation strategies.
• Enable intelligent operations and decisioning by translating unstructured business logic into structured knowledge artifacts, such as KPIs, rulesets, feature stores, and semantic models used by dashboards or AI agents.
• Serve as a strategic translator between complex business challenges and modern data architecture by leading domain-level and cross-domain data product strategy engagements.
• Lead the design of enterprise-grade data products that align with OKRs, business transformation goals, and operational needs ensuring value realization across functional areas like supply chain, marketing, store ops, or customer satisfaction.
• Architect and operationalize a unified enterprise-wide semantic layer, metrics store, and business logic abstraction that powers dashboards, self-service analytics, and machine-readable APIs.
• Lead initiatives to unify KPIs, standardize metric definitions, and streamline business logic through reusable models.
• Design composable data assets and feature stores that enable real-time and offline access patterns for ML models, AI agents, and decision orchestration systems.
• Lead readiness initiatives for integrating data…