About Coursera + Udemy
Coursera and Udemy are now one company, bringing together two mission-driven brands to create the world’s most powerful platform for turning learning into progress. Together, we help more than 300 million learners and 12,000+ enterprise customers build the skills they need for a world being reshaped by AI. Read more about the combined company by visiting our blog.
Why join us now?
AI is transforming how people learn, work, and grow, and the need for new skills has never been greater. Coursera brings trusted content and credentials from leading university and industry partners, while Udemy brings a dynamic skills marketplace and global network of real-world experts. By combining these strengths, we can connect more people and organizations to the skills they need, when they need them.
Shape what comes next
By joining our team, you’ll have the opportunity to reshape how the world learns and applies skills—and help millions of people participate in the new economy. Bring your ideas, expertise, and perspective to meaningful work that can make a difference at global scale.
Job Overview:
Analytics Engineering plays a crucial role in building robust and reliable data pipelines and data models that enable data-driven decision-making, powering various analytics, AI, and machine learning initiatives within Coursera. In addition, Analytics Engineering today owns many external facing data products that drive revenue and boost partner and learner satisfaction.
As a Staff Analytics Engineer, you will be architecting high quality and scalable data pipelines powering business critical applications, leading enterprise wide data modeling strategies and driving a culture of transparent, well-governed data systems. You will collaborate with both technical and cross-functional leaders to lead and set direction on how we craft and look at data, while driving industry accepted standards on data governance, discoverability, and accessibility. You will craft technical decisions and design trade-offs to ensure we can speedily deliver on ambitious, innovative goals while building the foundations for extension and scale in years to come.
Responsibilities:
- Architect scalable data models and construct high quality ELT pipelines that act as the backbone of our core data lake, with cutting edge technologies such as Airflow, DBT, Databricks, and Sigma. Your work innovates with principles adopted by others.
- Design, build, and launch self-serve analytics products from data consumption to data discovery and enablement. Your creations reach far beyond basic dashboarding and are intimately tied with business outcomes, identifying root causes of trends that have immediate impact.
- Be a technical leader for the team. Your proficiency in technical and architectural designs for major team initiatives will inspire others. Help shape the future of Analytics Engineering at Coursera and foster a culture of continuous learning and growth.
- Be a data leader for the business. Your initiatives will directly increase data literacy, significantly reduce pain points, and resolve data gaps.
- Partner with data scientists, business stakeholders, and product engineers to define, curate, and govern high-fidelity data. Your ability to see KPI interrelationships and how they maximize ROI across the business makes you a recognized bridge connecting data and business outcomes.
- Develop new tools and frameworks in collaboration with other engineers. Your innovative solutions will enable our customers to understand and access data more efficiently, while enhancing frameworks with AI-driven capabilities.
Basic Qualifications:
- 10+ years experience in data/analytics engineering with expertise in data architecture, pipelines, and reportingExpert experience with relational databases, DRY data modeling practices, and efficient SQL code generation
- Expert experience with some of: AWS, Databricks, Delta Lake, Airflow, dbt, Redshift, Datahub; Databricks preferred, dbt required
- Expert experience with crafting and driving self service reporting solutions with hands on experience in BI Tools; Looker or Sigma preferred
- Strong understanding and demonstrated experience in root cause analysis, with a background in Data Science or Business a plus
- Strong experience implementing Data Observability frameworks (e.g., Monte Carlo, Great Expectations) at an enterprise level
- Strong hands on experience with AI tools such as Claude, Gemini, Cursor and its role in streamlining data processing and enabling data democratization
- Strong experience with data lake architecture and batch and streaming architectures
- Strong experience in driving industry standards in data governance and technical best practices and driving standards across multiple engineering pods or business disciplines
- Strong ability to communicate technical concepts clearly and concisely to leadership
- Proven relationships with business end users with clear understanding of how data is used to power business decisions with demonstrated storytelling skills connecting data with trends observed in business
- Independence and passion for innovation and learning new technologies; seeks out and creates high-impact projects
Preferred Qualifications:
- Strong Experience leading cross-functional RFCs (Request for Comments) and driving technical standards across multiple engineering pods or business disciplines
- Strong experience with data lake architecture and batch and streaming architectures
- Proven track record building feature stores or data pipelines specifically for LLM fine-tuning and RAG architectures
- Strong track record of leadership and mentorship in elevating data culture, preferably in a remote environment
If this opportunity interests you, you might like these courses on Coursera:
- Big Data Specialization
- Generative AI Fundamentals
- Data Warehousing for Business Intelligence
Compensation / Location:
At Coursera, we offer competitive, zone-based pay aligned to your location, experience, and role level. Our total rewards package goes beyond salary, with comprehensive health and wellness benefits, bonus and RSU equity programs, and global perks designed to help you grow and thrive wherever you are.
This role is only available for hire in:
US Zone 3: $167,200 - $209,000
US Zone 4: $156,000 - $195,000
US Pay Zones:
- US-Z1: SF Bay Area (within 75 miles)
- US-Z2: NYC and Seattle Metro (within 75 miles)
- US-Z3: CA, WA, NY, NJ, CO, CT, DC, GA, IL, MA, MD, OR, RI, TX, VA
- US-Z4: AK, AZ, DE, FL, HI, ID, IN, IA, KS, KY, MI, MN, MO, MT, NC, NV, NH, OH, OK, PA, SC, TN, UT, VT, WI
Application Window: September 2nd - September 9th
We anticipate the application window will be open until September 9th. Based on business needs, this opportunity may remain posted beyond or closed before the anticipated application window.
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For more information about how Coursera collects and uses your personal information, please see our Coursera + Udemy Global Applicant Privacy Notice.
To protect against recruitment fraud, Coursera + Udemy recruiters only communicate via official coursera.org/udemy.com email addresses and never through personal accounts. We do not accept resumes via email or social media; please submit all applications directly through our careers page.
If you encounter suspicious recruitment activity, please report it via our Fraudulent Activity Submission Form.
Coursera is an Equal Opportunity Employer committed to building a welcoming and inclusive workplace. We consider all qualified applicants without regard to legally protected characteristics and provide reasonable accommodations upon request at [email protected].
Skills Required
- 10+ years of experience in data or analytics engineering, including data architecture, pipelines, and reporting
- Expertise with relational databases, DRY data modeling practices, and efficient SQL code generation
- Expert experience with AWS, Databricks, Delta Lake, Airflow, dbt, Redshift, or DataHub; dbt is required
- Expert experience creating and driving self-service reporting solutions with hands-on BI tool experience
- Strong understanding and demonstrated experience in root-cause analysis
- Strong experience implementing enterprise data observability frameworks such as Monte Carlo or Great Expectations
- Strong hands-on experience with AI tools such as Claude, Gemini, and Cursor
- Strong experience with data lake architecture and batch and streaming architectures
- Strong experience driving data governance standards and technical best practices across multiple engineering pods or business disciplines
- Strong ability to communicate technical concepts clearly and concisely to leadership
- Proven relationships with business end users and understanding of how data powers business decisions, including data storytelling
- Independence, innovation, continuous learning, and ability to create high-impact projects
- Strong experience leading cross-functional RFCs and driving technical standards across multiple engineering pods or business disciplines
- Proven track record building feature stores or data pipelines for LLM fine-tuning and RAG architectures
- Strong leadership and mentorship experience in elevating data culture, preferably in a remote environment
- Background in Data Science or Business
- Experience with Databricks
- Experience with Looker or Sigma
Coursera + Udemy Compensation & Benefits Highlights
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Healthcare Strength — Comprehensive medical coverage is highlighted at Udemy, and mental-health support (e.g., Modern Health and similar resources) is explicitly called out. Coursera and Udemy materials consistently reference broad health and well‑being support as part of standard packages.
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Equity Value & Accessibility — Equity participation is emphasized through RSUs and an Employee Stock Purchase Plan, with Coursera’s 2026 proxy confirming an ESPP and job postings noting RSUs/bonuses. Being public tech companies, both signal accessible ownership as a core element of total rewards.
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Parental & Family Support — Family-building and parental policies are prominently featured, including Udemy’s lifetime reimbursement for fertility/adoption/surrogacy and fully paid parental leave. Coursera communications reference substantial paid parental leave and related supports as part of the package.
Coursera + Udemy Insights
What We Do
About Coursera: Coursera was launched in 2012 by Andrew Ng and Daphne Koller with a mission to provide universal access to world-class learning. Coursera partners with leading university and industry partners to offer a broad catalog of content and credentials, including courses, Specializations, Professional Certificates, and degrees. Coursera’s platform innovations — including AI-powered personalized guide and features, like Role Play and Course Builder, and role-based solutions like Skills Tracks — enable instructors, partners, and companies to deliver scalable, personalized, and verified learning. About Udemy: Udemy is an AI-powered skills acceleration platform transforming how companies and individuals across the world build the capabilities needed to thrive in a rapidly evolving workplace. By combining on-demand, multi-language content with real-time innovation, Udemy delivers personalized experiences that empower organizations to scale workforce development and help individuals build the technical, business, and soft skills most relevant to their careers.
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Coursera + Udemy Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
We offer hybrid work schedules and hybrid working so our people can make work fit their unique needs.
