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Director, Analytics Engineering
Coursera was launched in 2012 by Andrew Ng and Daphne Koller with a mission to provide universal access to world-class learning. Today, it is one of the largest online learning platforms in the world, with 191 million registered learners as of September 30, 2025. Coursera partners with over 375 leading universities and industry partners to offer a broad catalogue of content and credentials, including courses, Specializations, Professional Certificates, and degrees. Coursera’s platform innovations — including generative AI-powered features like Coach, Role Play, and Course Builder, and role-based solutions like Skills Tracks — enable instructors, partners, and companies to deliver scalable, personalized, and verified learning. Institutions worldwide rely on Coursera to upskill and reskill their employees, students, and citizens in high-demand fields such as GenAI, data science, technology, and business, while learners globally turn to Coursera to master the skills they need to advance their careers. Coursera is a Delaware public benefit corporation and a B Corp.
We’re a global platform aiming to transform lives through learning by offering transformative courses, certificates, and degrees that empower learners worldwide to advance their careers through skill mastery. We’re looking for inventors, innovators, and lifelong learners eager to shape the future of education. If you’re ready to build the global programs and tools that fuel the power of online learning, join Team Coursera.
At Coursera, we are committed to building a globally diverse team and are thrilled to extend employment opportunities to individuals in any country where we have a legal entity. We require candidates to possess eligible working rights and have a compatible timezone overlap with their team to facilitate seamless collaboration. As a remote-first company, our interviews and onboarding are entirely virtual, providing a smooth and efficient experience for our candidates.
Job Overview:
Coursera is committed to strengthening its data ecosystem to power strategic business initiatives and accelerate innovation in artificial intelligence across the organization. As part of this effort, we are developing a modern analytics layer designed to provide seamless access to trusted, timely insights that empower business users to make informed decisions with confidence.
The newly established Analytics Engineering team will play a pivotal role in this transformation—translating business needs into scalable, high-quality data models; promoting data adoption and literacy; and fostering a culture of data-driven decision-making across the company.
The Director of Analytics Engineering will lead a multidisciplinary team of business intelligence analysts and analytics engineers, ensuring that data is accessible, reliable, and actionable. This leader will collaborate closely with other data and technology leaders to define and execute a cohesive, forward-looking data vision for Coursera.
Responsibilities:
Leadership & Strategy
- Define and execute the vision and roadmap for analytics engineering and data enablement. Including data literacy education across the company.
- Partner with data science, product, finance, and other business teams to ensure robust data delivery for decision-making and experimentation.
- Drive adoption of best practices in data modeling, ETL/ELT, and metadata management.
Data Infrastructure & Architecture
- Oversee development and maintenance of data pipelines, data warehouses, and analytics tools (e.g., Databricks, dbt, etc.).
- Ensure data quality, integrity, and governance across all sources and models.
Team Management
- Build, mentor, and manage a team of analytics engineers and technical leads.
- Establish processes for collaboration, code review, and documentation.
- Promote a culture of continuous improvement, learning, and technical excellence.
Cross-Functional Collaboration
- Work closely with data scientists, analysts, and business stakeholders to deliver data products and analytics solutions.
- Translate complex business questions into technical requirements and data models.
- Advocate for data democratization and empower teams through self-service analytics.
Basic Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, or a related field.
- 10+ years of experience in data or analytics engineering, with 3–5 years in leadership roles.
- Proven experience designing and scaling cloud-based data infrastructure (AWS, GCP, or Azure).
- Expertise with SQL, Python, and modern data tools (dbt, Airflow, Looker, Tableau, etc.).
- Strong understanding of data modeling (Kimball, Data Vault), warehousing, and governance principles.
- Exceptional communication and leadership skills; ability to influence at all organizational levels.
Preferred Qualifications:
- Hands-on experience with AWS, Databricks, Delta Lake, Airflow, DBT, Redshift
- Background in a SaaS, tech, or digital product company.
- Familiarity with compliance and data privacy frameworks (GDPR, CCPA, etc.).
- Demonstrated success implementing data quality and observability programs.
If this opportunity interests you, you might like these courses on Coursera:
- Data Analytics Engineering: Probability & Techniques | Coursera
- The Path to Insights: Data Models and Pipelines | Coursera
- Data Management with Databricks: Big Data with Delta Lakes
[FOR US ROLES ONLY]
Compensation
US Zone 1: $234,800 - $293,500
US Zone 2: $224,400 - $280,500
US Zone 3: $208,000 - $260,000
The range(s) listed above is the expected annual base salary for this role, subject to change.
Salary is just one component of Coursera’s total rewards package. All regular employees are also eligible for a bonus program and equity in the form of RSU’s.
A number of factors are taken into account when determining pay, which includes: job level, location, training/education, business need, skill set and internal equity.
Current Zone Locations:
- Zone 1- San Francisco Metro, New York City Metro or Seattle Metro
- Zone 2 - CA (outside of SF Bay Area), CO, CT, DC, GA, IL, MA, MD, NY/NJ (other than NYC), OR, RI, TX, VA, WA (other than Seattle)
- Zone 3 - all other US locations
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