Senior Cloud Data Warehouse Engineer

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WW is looking for candidates to help change people’s lives. We are a global wellness technology company inspiring millions of people to adopt healthy habits for real life. We do this through engaging digital experiences, face-to-face workshops and sustainable programs that encourage people to move more, shift their mindset and eat healthier while enjoying the foods they love. By drawing on over five decades of experience and expertise in behavioral science, we build communities in order to deliver wellness for all.

Who we are

The Data Warehouse Engineering team has one aim - end to end ownership of all analytics needs of WW from sourcing data from anywhere as needed, to transforming the data into analyzable structures at scale - by building generic configurable data applications, to empowering the analytics , product and business teams to leverage the data to better help members in their wellness journey

Thus our mission and guiding principle is “We are going to treat data as a product, if end users don't flock to it, we haven't built it well enough. Adoption comes from building something so accurate, timely, reliable, accessible and innovative that everyone wants to use it”

What you will do

  • Build Kafka consumer data applications

  • Push the envelope with Snowflake data platform 

  • Create complex yet maintainable workflows in Prefect using python 

  • Leverage new stack concepts such as ReverseETL to empower Marketing teams using platforms like HighTouch 

  • Rethink how Python and SQL can work together to tame data challenges

  • Creatively solve for Data Observability leveraging things like DataDog, OpenTelemetry , MonteCarloData, Anomolo or equivalent 

  • Create reusable , inheritable models in Looker that serves broad use cases from direct exploration and dashboarding to serving as a logical data layer for various integrations

Who you are

We understand that no one can be an expert in everything, but be an Senior Engineer in DWE, ideally, you have: 

  • 5+ years of experience in aspects of data engineering along with at least 2 years in cloud native Data Warehouse technologies 

  • experience with building SQL based DW systems

  • experience in writing modular , testable , though complex , ELT and ETL pipelines 

  • leverage a high level language - ideally Python, to build data applications

  • Wrestled with the trade offs involving design of data warehouses or data applications

#LI-Remote 

At WW, it is our priority to cultivate a diverse and inclusive workplace. We are committed as individuals, as an organization, and as fellow humans, to advocate for and support our employees, our members, and our communities. We are proud to be an equal opportunity employer and we do not discriminate on the basis of sex, race, color, creed, national origin, marital status, age, religion, sexual orientation, gender identity, gender expression, veteran status, or disability.

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Candidate Location Eligibility:
Albuquerque, NM
Ann Arbor, MI
Atlanta, GA
Austin, TX
Baltimore, MD
Baton Rouge, LA
Birmingham, AL
Boise, ID
Boston, MA
Buffalo, NY
Charleston, SC
Charlotte, NC
Chicago, IL
Cincinnati, OH
Cleveland, OH
Colorado, CO
Columbus, OH
Dallas-Fort Worth, TX
Dayton, OH
Des Moines, IA
Detroit, MI
Fayetteville-Springdale-Rogers, AR
Greensboro, NC
Hampton Roads, VA
Hartford, CT
Houston, TX
Huntsville, AL
Indianapolis, IN
Jacksonville, FL
Kansas City, MO
Las Vegas, NV
Lexington, KY
Lincoln, NE
Little Rock, AR
Los Angeles, CA
Louisville, KY
Madison, WI
Memphis, TN
Miami, FL
Milwaukee, WI
Minneapolis–Saint Paul, MN
Nashville, TN
New Orleans, LA
New York City, NY
Ogden, UT
Oklahoma City, OK
Omaha, NE
Orlando, FL
Other US Location
Palm Bay-Melbourne-Titusville
Pensacola, FL
Peoria, IL
Philadelphia, PA
Phoenix – Mesa – Scottsdale, AZ
Pittsburgh, PA
Portland, ME
Portland, OR
Providence, RI
Provo, UT
Raleigh-Durham, NC
Reno, NV
Richmond, VA
Rochester, NY
Sacramento, CA
Salt Lake City, UT
San Antonio, TX
San Diego, CA
San Francisco, CA
San Luis Obispo, CA
Santa Cruz, CA
Seattle, WA
Spokane, WA
St. Louis, MO
Tallahassee, FL
Tampa Bay, FL
Tucson, AZ
Tulsa, OK
Washington DC
Wichita, KS
Wilmington, NC

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