Director Data Engineering

Ascend Learning, LLC•Burlington, OR

3d•$178,900 - $255,860•Hybrid

About The Position

The Director Data Engineering is responsible for leading and managing technical resources and teams to design, build, and maintain scalable data infrastructure, pipelines, and quality measures across the enterprise. This includes building strong working relationships with business leadership and business intelligence leaders. This role aims to drive technical strategy, optimize data architecture, and ensure the alignment of data engineering initiatives with business goals to enable data to create a competitive edge for our company. Additionally, the role involves being knowledgeable of the latest data engineering technologies and building teams that are proficient in the technologies in place and in the marketplace.

Requirements

High School Diploma or GED Required.
A minimum of 7-10 years of relevant professional experience in data engineering, data architecture, software engineering, or a related area.
Proven experience in leading and managing technical teams.
Strong executive presence with the ability to represent the Data Engineering function to internal and external stakeholders, including cross-functional Senior Leadership
A track record of successful implementation of enterprise data engineering projects and strategies within an organization.
Experience with data infrastructure in a business context, demonstrating a strong understanding of how data platforms and pipelines can solve real-world problems and drive value.
Experience working collaboratively between data engineering and business intelligence teams.
Prior experience in a senior role, such as a Lead Data Architect, Data Engineering Manager, or similar leadership position in the field of data engineering.
Strong expertise in data architecture, modeling (ERDs, dimensional modeling), and data integration across systems.
Proficiency with data pipelines and transformation tools (e.g., Azure Data Factory, Coalesce, Snowpipe) and version control (e.g., GitLab).
Knowledge of cloud computing platforms (e.g., AWS, Azure, Google Cloud) that offer data and analytics services.
Experience with BI and analytics tools (e.g., Tableau, Python, R) and advanced analytics techniques.
Familiarity with DataOps/DevOps practices and automation tools (e.g., Terraform, ARM).
Understanding of data governance, security, and best practices.
Knowledge of Agile/Scrum methodologies and tools (e.g., JIRA, Confluence).
Excellent communication and interpersonal skills to effectively lead teams and interact with stakeholders.
Strong analytical and problem-solving abilities.
Strategic thinking and business acumen to align data engineering initiatives with organizational goals.
Continuous learning mindset to keep up with the rapidly evolving field of data engineering.

Nice To Haves

Bachelor's degree in Computer Science, Data Engineering, Information Systems, Software Engineering, or a related technical field preferred.
Experience with AI/ML and familiarity with modern AI platforms (e.g., Azure ML, Copilot, Claude, OpenAI) is preferred.

Responsibilities

Build, mentor, and oversee specialized team(s) of data engineering professionals, including data engineers, specialized senior data engineers, and data architects.
Define clear roles, establish performance metrics, and promote ongoing learning to cultivate a team that is proficient in state-of-the-art data engineering technologies and methodologies.
Maintain cutting-edge knowledge of data engineering trends and advancements, leading the exploration and integration of new technologies and practices.
Evaluate the potential benefits and risks of new technologies to the organization and drive the adoption of transformative data solutions that can revolutionize platform and infrastructure capabilities.
Manage the end-to-end execution of data engineering projects, ensuring they adhere to high standards of quality, meet established timelines, and stay within budget.
Oversee project lifecycles, from conception through to deployment, while continuously monitoring progress and making strategic adjustments as necessary.
Encourage cross-departmental collaboration and serve as the data engineering advocate within the organization.
Communicate complex technical concepts and insights to stakeholders at all levels, ensuring a cohesive understanding and integration of data capabilities across various business units to drive informed decision-making and policy development.
Identify data-driven opportunities, set objectives, and create a roadmap for implementation to ensure the organization capitalizes on data engineering innovations for competitive advantage.
Establish and enforce robust data governance frameworks to ensure secure, reliable, and accountable management of data assets within the organization.
Develop policies for data privacy, data quality, and lineage, as well as setting up oversight mechanisms to monitor data systems for compliance with legal and regulatory standards.
Promote trust and integrity in the organization's data, safeguarding the interests of the company and its stakeholders while fostering responsible innovation.