Data Engineering Lead

About OpenSesame

While it appears to most people that we just sell training courses (over 50,000 of them), what we really offer is the opportunity for companies to upgrade the skills of each of their employees and reinvent their workforce in an AI world. We have strategic partnerships with 150+ Global 2000 companies who rely on our training programs to develop the world's most productive and admired workforces. Now we are building what comes next. 

About the Team

The Data Engineering Lead will guide a lean and focused data engineering team. The team’s mission is to build and scale an AI-ready data foundation that enables reliable analytics, operational reporting, governance, and future AI initiatives across the company. 

This role partners closely with analysts, business leaders, platform teams, and data consumers company-wide to improve accessibility, trust, and usability of enterprise data assets.

About the Role 

This role owns the Data Governance & Accessibility program and serves as the technical leader responsible for designing scalable data architecture, improving pipeline reliability, mentoring data engineers, and enabling analysts through robust, specialized data solutions. Success in this role requires balancing hands-on technical leadership with strategic planning, cross-functional influence, and operational excellence.

Performance Objectives

30 Days

• Develop a comprehensive understanding of OpenSesame’s current data ecosystem, governance practices, reporting dependencies, and analyst workflows. 
• Conduct a full assessment of existing pipelines, warehouse architecture, data quality gaps, lineage visibility, and AI-readiness constraints.
• Establish working relationships with analytics stakeholders across departments and create a prioritized roadmap for improving governance, accessibility, and platform scalability while aligning the two-person engineering team around delivery standards and operating rhythms.

60 Days

• Design and begin implementing the foundational architecture for an AI-ready data platform, including standardized ingestion patterns, governance controls, metadata management, and scalable transformation frameworks. 
• Introduce monitoring, alerting, and documentation standards that improve reliability and analyst trust in shared datasets. 
• Mentor the Data Engineers through structured technical reviews, backlog prioritization, and development planning while improving delivery velocity and reducing operational bottlenecks for analyst requests.

90 Days

• Launch the first phase of the Data Governance & Accessibility program by delivering production-ready, well-documented pipelines and certified datasets that support multiple business functions.
•  Establish company-wide standards for data ownership, quality monitoring, lineage tracking, and access management.
• Demonstrate measurable improvements in analyst efficiency, data reliability, and pipeline performance while creating a sustainable technical mentorship model that elevates engineering quality, promotes knowledge sharing, and prepares the organization for future AI and advanced analytics initiatives.

6 Months

• Deliver a scalable and extensible data platform capable of supporting advanced analytics, machine learning experimentation, and AI-powered business initiatives.
• Establish governance processes that enable self-service analytics while maintaining strong security and data quality standards. 
• Create a high-performing engineering culture centered on technical excellence, operational discipline, and continuous improvement, with clear ownership models and repeatable delivery practices across the data organization.

Success in the Role Looks Like

• Analysts across the company can reliably access trusted, well-documented datasets with minimal engineering intervention.
• Data pipelines operate with strong observability, measurable SLAs, and reduced operational failures.
• Governance standards are consistently applied across core business domains.
• The data platform is structured to support future AI and machine learning initiatives without major architectural redesign.
• The engineering team demonstrates improved delivery consistency, technical maturity, and collaborative execution.
• Stakeholders view the data organization as a strategic enabler rather than a reactive support function.

You might notice we don’t list a traditional set of requirements or buzzwords here. That’s intentional.

We’re looking for proven examples from your career that show you can build brands, create scalable systems, and drive measurable marketing impact. When you look back a year from now, you’ll know you’ve elevated OpenSesame’s brand and strengthened its market presence.

Location: This position can be based anywhere in the US. We operate as a remote-first company and invest in all-company in-person meetings several times a year. 

Performance Driven: We're looking for self-starters with a track record of delivering excellent results, but we're highly selective about who we hire. We don't focus on typical job requirements; instead, we're interested in specific examples from your past experiences. All positions can be based anywhere in the US, and require up to 15 days of travel per year, with senior management and leadership teams requiring up to 35 days.

Compensation: The salary for this role range between $150,000 - $170,000  per year, depending on experience. At OpenSesame, we offer a comprehensive benefits package to employees upon hire, including professional development, ISOs, health insurance, 401(k) matching, and paid time off. We carefully consider a wide range of compensation factors, relying on market data to determine compensation and consider your specific job family, background, skills, and experience. We prioritize pay transparency, fairness, and equity to create a positive and inclusive work environment, regularly reviewing our compensation practices to align with our values and goals.

Equal Employment Opportunity: OpenSesame is an Equal Employment Opportunity and Affirmative Action employer that values and welcomes diversity. We do not discriminate on the basis of various legally protected characteristics, including criminal history, and strive to provide reasonable accommodations to qualified individuals with disabilities. We prioritize safety and security and may use your information accordingly, and you can contact us for assistance or accommodations during the job application process. 

Pay Transparency: At OpenSesame, we prioritize pay transparency, fairness, and equity to create a positive and inclusive work environment, regularly reviewing our compensation practices to align with our values and goals. We provide competitive and fair compensation to our employees based on their skills, experience, and performance.

CPRA (California Candidates): When you submit your application, OpenSesame may collect and use your personal information in accordance with our privacy policy and the CPRA. This may include personal details and employment history, and will only be used for employment-related purposes. We may share this information with third-party service providers, but we will not sell it to third parties. If you have any questions or concerns, please contact us, and for more information on your rights under the CPRA, refer to our privacy policy or the California Attorney General's website.

We Care About Your Security: We’ve been made aware of a phishing scam involving individuals impersonating OpenSesame recruiters. All legitimate communication from our team will come from @opensesame.com email addresses. If you receive a suspicious message, please contact us directly at careers@opensesame.com. Your security matters to us — thank you for staying vigilant