Director, Data Engineering (Remote)

The application window is anticipated to close 4/10/2025.

Duties & Responsibilities:

• Lead the migration from on-premises data center to Azure, including developing a comprehensive migration strategy, coordinating with other departments, and ensuring that the migration is completed within agreed-upon timelines and budget.
• Manage the data engineering department, including developing and managing the department's budget and resources, providing leadership and guidance to the team, and ensuring that the team's work aligns with the organization's overall data strategy and business objectives.
• Develop and implement a data engineering strategy, including defining and prioritizing the department's goals and objectives, identifying opportunities to leverage Azure services to improve data infrastructure and processes, defining and implementing data governance and data quality best practices, and ensuring that the department's work is aligned with industry best practices and emerging trends.
• Design and maintain data architecture, including data warehousing, data marts, and ELT pipelines, ensuring that the data architecture is scalable, flexible, and optimized for performance and efficiency.
• Ensure data quality and governance, including establishing data quality checks and controls, defining and implementing data access controls and compliance with data privacy regulations, developing and maintaining data dictionaries and data catalogues, and ensuring that data governance policies are adhered to.
• Drive innovation and continuous improvement, including staying up-to-date with emerging technologies and industry trends, identifying opportunities to improve processes and workflows within the department, and fostering a culture of innovation and continuous improvement within the department.
• Collaborate with other departments, including data analytics and business intelligence, IT and security, and legal and compliance, to ensure that the organization's data infrastructure is meeting their needs and aligned with the organization's overall data strategy and business objectives.
• Stay current with Azure technologies, including staying up-to-date with Azure technologies and services, participating in Azure communities of practice, and attending relevant conferences and seminars to stay current with emerging trends and best practices.

Knowledge, Skills, and Abilities:

• Deep expertise in designing and managing modern data architectures, including data lakes, warehouses, and ETL/ELT processes.
• Strong proficiency with SQL and experience in cloud-based data platforms (e.g., AWS, Azure, Google Cloud).
• Proven track record of implementing big data technologies like Spark, Hadoop, or Kafka.
• Experience with relational and NoSQL databases (e.g., PostgreSQL, MongoDB, Redshift).
• Familiarity with BI and analytics tools (e.g., Power BI, Tableau, Looker).
• Solid understanding of data governance principles and tools.
• Exceptional leadership and communication skills.
• Ability to influence and collaborate with technical and non-technical stakeholders.
• Strong problem-solving and critical-thinking abilities.
• Commitment to fostering an inclusive, innovative, and high-performing team culture.
• Experience with cloud-based data platforms, such as Azure or AWS.
• Experience with data warehousing, data marts, ELT pipelines, and data governance best practices.
• Strong leadership and people management skills.
• Excellent communication and collaboration skills.
• Ability to manage multiple priorities and meet deadlines in a fast-paced environment.
• Experience in higher education or related field.
• Experience with Azure Data Factory, Azure Data Lake, and Azure Synapse Analytics.
• Experience with agile development methodologies.
• Experience with data visualization and business intelligence tools.

Minimum Qualifications:

• Bachelor’s degree in Computer Science, Engineering, or a related field or equivalent advanced learning attained through professional level experience required.
• Minimum 7 years of experience in data engineering, data architecture, or a related field, including 3 years of managerial experience, or equivalent combination of education and work experience.

Preferred Qualifications:

• Master’s degree in Computer Science, Engineering, Data Science, or related field.
• Experience with machine learning pipelines and AI integration.
• Knowledge of Infrastructure as Code (IaC) tools like Terraform or CloudFormation.
• Certifications in relevant cloud platforms or data technologies (e.g., AWS Certified Data Analytics, Microsoft Certified Data Engineer).