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Director, Data and Integrations

LinkedIn Western National Insurance Edina, MN
Not Applicable Posted March 26, 2026 Job link
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Requirements
  • Ten-plus years of experience in data engineering, integration development, or related technical disciplines.
  • Ten-plus years of leadership experience managing technical teams, including people leaders.
  • Demonstrated experience architecting and delivering enterprise-scale data and integration solutions.
  • Proven track record establishing engineering standards, driving platform modernization, and improving operational reliability.
  • Deep expertise in modern cloud data platforms (e.g., cloud-native data warehouses / lakehouse platforms), ETL / ELT frameworks, data lakes / lakehouses, and real-time streaming architectures, including hands-on experience leading large-scale platform migrations.
  • Proficiency with integration technologies (APIs, microservices, middleware, messaging platforms, event-driven architecture).
  • Understanding of database systems (SQL / NoSQL), data modeling, and metadata management.
  • Experience with CI / CD pipelines, DevOps practices, test automation, and infrastructure-as-code.
  • Familiarity with cloud providers (AWS, Azure, or equivalent) and hybrid-cloud data / integration architectures.
  • Knowledge of security, compliance, and data governance frameworks.
  • Experience architecting data platforms to support AI / ML pipelines, feature stores, and model operationalization (MLOps).
  • Familiarity with AI / ML tooling ecosystems and integration patterns between data platforms and data science environments (e.g., Databricks, SageMaker, Python-based ML stacks).
  • Understanding of cost optimization strategies in cloud-native data platforms.
  • Enterprise leadership and ability to influence across organizational boundaries.
  • Strong communication skills for both executive audiences and technical teams.
  • Strategic planning, prioritization, and portfolio management skills.
  • Deep understanding of data lifecycle, integration architectures, and modern engineering practices.
  • Ability to foster a culture of continuous improvement and operational excellence.
  • Vendor, contract, and budget management.
  • Background in enterprise architecture or platform engineering.
  • Experience implementing Master Data Management (MDM), API gateways, or enterprise service buses.
  • Familiarity with analytics, BI platforms, and data science enablement.
  • Demonstrated experience leading enterprise data platform modernization programs.
  • Experience enabling AI initiatives, including predictive analytics, machine learning, or generative AI use cases.
  • Experience building or supporting enterprise data science capabilities at scale.
Preferred Skills
  • Background in enterprise architecture or platform engineering.
  • Experience implementing Master Data Management (MDM), API gateways, or enterprise service buses.
  • Familiarity with analytics, BI platforms, and data science enablement.
  • Demonstrated experience leading enterprise data platform modernization programs.
  • Experience enabling AI initiatives, including predictive analytics, machine learning, or generative AI use cases.
  • Experience building or supporting enterprise data science capabilities at scale.
  • Master’s degree or MBA preferred.
Education
  • (Required) – Bachelor’s degree in computer science, information systems, engineering, or related technical field required.
  • (Not required) – Background in enterprise architecture or platform engineering.
  • (Not required) – Master’s degree or MBA preferred.