About the role
United States
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.
Why join us now?
AI is transforming how people learn, work, and grow, and the need for new skills has never been greater.
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.
Design, build, and launch self-serve analytics products from data consumption to data discovery and enablement.
Be a technical leader for the team. 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.
Develop new tools and frameworks in collaboration with other engineers.
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 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
Strong ability to communicate technical concepts clearly and concisely to leadership
Proven relationships with business end users
Independence and passion for innovation and learning new technologies
Preferred Qualifications:
Strong Experience leading cross-functional RFCs and driving technical standards
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
Compensation / Location:
This role is only available for hire in:
US Zone 3: $167,200 - $209,000
US Zone 4: $156,000 - $195,000
Minimum requirements
- 10+ years in data/analytics engineering with expertise in data architecture, pipelines, SQL, and DRY data modeling
- Expert in AWS, Databricks (preferred), dbt (required), Airflow, and BI tools like Looker or Sigma
- Strong experience in data governance, observability frameworks, AI tools, and clear communication with leadership
This listing was parsed by AI and may not be complete. Check the official posting on Coursera's site for the most accurate information.