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Data Engineer


As Scale’s Data Engineer, you will spearhead building Scale’s analytical and business-intelligence infrastructure. Scale’s customers process millions of tasks through our APIs, and we’re looking for a talented Analytics Engineer to build scalable solutions to support this growth. You will have widespread purview, with responsibility for understanding, mining, aggregating, and exposing data across the entire business to support timely and efficient decision-making and data exploration. You will also implement Scale’s data warehouse, data mart, and business intelligence reporting environments, and help users transition their workflows to these systems.

You will:

  • Work with analytics, infrastructure, finance, and other business partners to drive the development of reporting and analytics platform
  • Establish business intelligence best practices, and build pipelines that provide single-source-of-truth foundational accuracy
  • Partner with operations and sales teams to automate manual workflows
  • Continually improve ongoing data pipelines and simplify self-service support for business stakeholders
  • Perform regular system audits to ensure complete and accurate reporting of data/metrics
  • Design and build visualization dashboards to accelerate information-to-action at scale

Ideally you'd have:

  • 5+ years of relevant work experience in a role requiring application of data modeling and analytic skills
  • A clear passion for learning new BI skills and techniques independently and continuously
  • Experience with ETL tools and building / maintaining a data warehouse
  • Experience in designing and building data infrastructure/automated reporting tools (Tableau)
  • Ability to create extensible and scalable data schema that lay the foundation for downstream analysis
  • Advanced data analysis knowledge and experience, with strong SQL, and data mining skills
  • Advanced knowledge and hands-on experience leveraging Python, and/or R to perform in-depth data analysis
  • Fluent in written and spoken English

Nice to haves:

  • Experience in using highly scalable data engineering technologies such as AWS, Airflow, Dagster, DBT
  • Experience in best practices in table partitioning/data sharding strategies and query optimization
About Us:At Scale, we believe that the transition from traditional software to AI is one of the most important shifts of our time. Our mission is to make that happen faster across every industry, and our team is transforming how machine learning can build innovative products. Our products provide access to human-powered data for hundreds of use cases and are used by industry leaders such as Open AI, Lyft, GM, Samsung, Airbnb, NVIDIA, and many more. We’ve recently raised $325 million in Series E funding at a valuation of $7B+ and are expanding our team to accelerate the development of AI applications. 
We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com [1]. Please see the United States Department of Labor's EEO poster [2] and EEO poster supplement [3] for additional information.

  1. http://accomodations@scale.com/
  2. https://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf
  3. https://www.dol.gov/ofccp/regs/compliance/posters/pdf/OFCCP_EEO_Supplement_Final_JRF_QA_508c.pdf

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