Staff Analytics Engineer
About Coursera
Coursera and Udemy are now one company, creating one of the world's most comprehensive skills development platforms for the AI era. This strengthens our ability to accelerate AI-powered innovation and shape how the world discovers and builds skills at a pivotal moment of change. Read more about the combined company by visiting our blog.
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. 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. Coursera recently combined with Udemy to create one of the world’s most comprehensive skills development platforms.
Why Join Us
At Coursera, we’re looking for inventors, innovators, and lifelong learners ready to shape the future of education. You’ll help build global programs and tools that power online learning for millions turning bold ideas into real impact. People who thrive here are customer-first builders who move fast, simplify ruthlessly, and iterate relentlessly on the metrics that matter.
We’re a globally distributed team that comes together intentionally for collaboration, complex problem-solving, and key milestones — creating opportunities for teams to do their best work together. Our virtual hiring and onboarding experience makes it easy to join us and start making an impact from anywhere. If you’re ready to make a global impact, help scale unique products across Coursera + Udemy, and grow your career, apply below.
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 reporting. Expert 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 and dbt preferred
- Expert experience with crafting and driving self service reporting solutions with hands on experience in BI Tools; Looker or Sigma preferred
- 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
Keep Learning
If this opportunity interests you, you might like these courses on Coursera:
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 [insert location]
- US Zone 1: $188,000 - $235,000
- US Zone 2: $182,000 - $228,000
- US Zone 3: $167,000 - $209,000
- US Zone 4: $156,000 - $195,000
US Pay Zones:
- US-Z1: 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
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Data & ML pay context
Based on 1,386 disclosed Data & ML salaries on RoleSuite, the role pays a median of $165K/year, with most offers between $128K and $209K (10th–90th percentile: $106K–$246K).
This posting lists $188K–$235K, above the $165K market median.
See the full Data & ML salary breakdown →