[Remote] Staff Analytics Engineer
Note: The job is a remote job and is open to candidates in USA. Coursera is a leading skills development platform that aims to provide universal access to world-class learning. The Staff Analytics Engineer will architect scalable data models and pipelines, collaborate with technical and cross-functional leaders, and drive data governance to enhance data-driven decision-making across the organization.
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
Skills
- 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
- 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
Benefits
- Comprehensive health and wellness benefits
- Bonus and RSU equity programs
- Global perks designed to help you grow and thrive wherever you are
Company Overview
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