DIRECTOR, DATA ENGINEERING

Min

USD $63.32/Hr.

Max

USD $101.32/Hr.

Overview

The Director of Data Engineering leads the strategy, design, and execution of the organization’s data architecture, pipelines, and platforms. This role oversees the development, optimization, and governance of enterprise data assets to ensure reliability, scalability, security, and performance. The Director partners closely with analytics, application development, data science, and operational leaders to deliver high-quality data products that enable advanced analytics, operational efficiency, and strategic decision-making. The role manages a high-performing team of data engineers and architects, drives adoption of modern cloud and data engineering standards, and ensures compliance with regulatory and organizational data governance requirements.

Please note this position is onsite in Springfield, IL.

Qualifications

Minimum Qualifications:Education:• Master’s degree or higher in the studies of Computer Science, Information Systems, Software Engineering, Data Engineering, or other related field.Licensure/Certification/Registry:• Certification in relevant cloud-based data platform technologies preferredExperience:• 7–10+ years of progressive experience in data engineering, data architecture, or enterprise data management, with at least 3–5 years in a formal leadership or managerial role.• Experience with cloud data platform technologies (Databricks or Microsoft Fabric) preferred.Other Knowledge/Skills/Abilities:• Proven experience designing, building, and optimizing enterprise-scale data pipelines, ETL/ELT workflows, and data integration architectures.• Demonstrated leadership in cloud-based data ecosystems (e.g., AWS, Azure, GCP), including data lakes, data warehouses, and streaming data services.• Experience establishing data quality, metadata management, data lineage, and governance frameworks.• Successful track record leading cross-functional teams and collaborating with Information Services, analytics, and business stakeholders.• Expertise in managing staff across the department to ensure timely delivery of services, and productive usage of staff and resources.• Ability to execute projects from start to finish including the development, measurement and reporting of key performance indicators and commitment to continuous quality improvement required.• Strong written and verbal communications skills, in order to explain to stakeholders, the insights drawn from analysis• Possesses a working knowledge of the enterprise application system and database portfolio, including development technologies, application design strategies, access methods, naming standards, performance tuning, and integration strategies necessary to maintain information integrity, security and physical storage requirements.• Possesses an expert knowledge of logical and physical data modeling, and leverages these skills to ensure consistent and efficient application of technologies.

 

Responsibilities

 

Principle Duties & Responsibilities:1. Develop and lead the enterprise data engineering strategy, ensuring alignment with organizational priorities, analytics needs, and digital transformation goals.2. Provide leadership to a team of data engineers, architects, and integration specialists, cultivating a high-performance culture focused on reliability, innovation, and continuous improvement.3. Partner with executive stakeholders to define the long-term roadmap for data platforms, infrastructure modernization, and emerging capabilities such as real-time analytics, interoperability, and AI/ML enablement.4. Architect, implement, and maintain scalable data platforms including data lakes, data warehouses, and streaming data environments.5. Oversee the design and execution of robust ETL/ELT pipelines and integration frameworks that ensure timely, accurate, and governed data across the enterprise.6. Evaluate and implement modern cloud-native technologies to strengthen system performance, resiliency, and scalability.7. Establish and enforce data quality standards, metadata management practices, and enterprise data governance policies in partnership with Information Services and data governance committees.8. Ensure data architecture complies with security and regulatory requirements (e.g., HIPAA, HITECH, CMS, SOC2).9. Monitor data reliability, integrity, and lineage, implementing processes to prevent data drift, inconsistencies, and quality degradation.10. Lead the development and maintenance of production-grade data integrations, pipelines, and workflows that support operational reporting, analytics, and regulatory submissions.11. Implement engineering best practices including version control, CI/CD automation, testing frameworks, and infrastructure-as-code.12. Manage workload prioritization, capacity planning, and service-level expectations to ensure timely delivery of data products and system enhancements.13. Partner