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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: 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 [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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Compétences linguistiques
- English
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