Director of Data & AI Platform Engineering
| Company | Akumin |
|---|---|
| Location | Seattle, WA, USA, Los Angeles, CA, USA, New York, NY, USA, Denver, CO, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | Bachelor’s |
| Experience Level | Senior, Expert or higher |
Requirements
- Bachelor’s Degree
- 12+ years of professional experience and 4+ years of management experience, with 5+ years managing Google based big data solutions; Experience with cloud data platforms is required
- Deep knowledge of database systems, data modeling, and ETL/ELT processes
- Hands-on experience working with and Mastery of CI/CD tools such as GitHub Actions, including their configuration, customization, and integration capabilities in progressively challenging roles
- Strong proficiency in scripting languages such as Bash, Python, or Groovy for automation and customization of CI/CD workflows
- Experience in seamlessly integrating containerization into CI/CD pipelines, registry management, and container orchestration platforms such as Kubernetes, Google DevOps including cluster setup, configuration, and management.
- Strong working knowledge and hands on experience with Google Cloud including Functions, DLS, and others
- Proficiency in infrastructure automation tools like Terraform, for provisioning and managing CI/CD infrastructure.
- Excels in all facets of verbal and written communication; leads and inspires the team via open communication, effective listening, and strong collaborative networks; has excellent negotiation skills, is an expert coordinator, and has an ability to orchestrate change through influence.
- Works effectively in the face of stress, ambiguity, difficult situations, and shifting priorities all while championing the long-term architectural view; understands the need to shift focus and priorities as required and successfully leads others through periods of change.
Responsibilities
- Lead and mentor a team of engineers, fostering a culture of collaboration, innovation, and excellence. Provide guidance, support, and coaching to team members to ensure individual and team goals are met. Manage performance evaluations, career development, and succession planning for the team.
- Develop and execute a scalable data engineering strategy to support automation, personalization, and initiatives. Design and oversee data architecture, pipelines, and ETL processes to ensure high performance, data accuracy, and reliability. Ensure compliance with data governance policies, security standards, and regulatory requirements across all marketing data operations.
- Develop and implement a strategic roadmap for technology initiatives within the CI/CD pipelines & Container platform domains. Collaborate with stakeholders to understand business requirements and translate them into technology solutions that enhance employee experience. Stay abreast of industry trends and emerging technologies to continuously improve and innovate our platform technology offerings.
- Drive initiatives to enable self-service capabilities and automation across all supported technology areas. Identify opportunities to streamline processes, reduce manual efforts, and increase efficiency through automation.
- Optimize data pipeline performance and automate processes to improve speed, reliability, and cost-efficiency.
- Develop a robust data infrastructure to support analytics teams in generating insights and visualizations that enhance decision-making in marketing. Collaborate with analytics teams to standardize key metrics, KPIs, and dashboards, providing a unified view of performance. Enable advanced analytics capabilities, such as predictive modeling and machine learning, to drive more precise analysis.
- Manage relationships with technology vendors and service providers, ensuring alignment with organizational goals and objectives. Evaluate vendor performance, negotiate contracts, and drive value-added partnerships to support our technology initiatives. Lead and coordinate Enterprise License Agreements with vendors.
- Other duties as assigned by management.
Preferred Qualifications
- Experience with machine learning, predictive analytics, and AI-driven personalization.
- Familiarity with data privacy regulations (e.g., HIPPA) and best practices for data security.
- Background in customer data (CDP) or identity resolution platforms is a plus.