Data Science Engineer at BetterCloud

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BetterCloud has offices in New York, Atlanta, and San Francisco. We are currently seeking new talent in Salt Lake City, Denver, and Austin.

BetterCloud is the leading SaaS Management Platform (SMP) that enables IT professionals to discover, manage and secure the growing stack of SaaS applications in the digital workplace. With an expanding ecosystem of SaaS integrations, thousands of forward thinking organizations like Zoom, Walmart, and Square now rely on BetterCloud to automate processes and policies across their cloud application portfolio.

A pioneer of the SaaSOps movement, BetterCloud has built a community of more than 45K IT professionals who are embracing the new role of SaaSOps within IT organizations. The company launched the first-ever annual SaasOps-focused conference, Altitude, and publishes annually the definitive market research report, State of SaaSOps, on the market and category.

BetterCloud is headquartered in New York City with offices in San Francisco, CA and Atlanta, GA.  The company's total amount raised to date is $187 million. Investors include Warburg Pincus, Accel, Bain Capital Ventures, Flybridge Capital Partners, and Greycroft Partners.

BetterCloud is seeking an enterprising individual to join the Platform Services team as a Data Science Engineer. If you are eager to learn, want to accomplish challenging goals, and thrive in a work-hard/play-hard environment then this is the position for you!

  • Primary responsibility for soundness of database pipeline design against standards for development, security and performance
  • Ownership of setting up process and frameworks to codify best practices -data extraction, transformations, load and data lake modeling and governance.
  • Provide and maintain portal for data analytics, metrics and query big data to help development teams
  • Create a Machine Learning Model to solve business operations problems like pattern or anomaly detection. And also develop many other models for in app features.
  • Responsible to develop and Maintain ML operations in production.
  • Work with multiple teams like development, product, security and BI to understand data sources and channel them into Data Lake.
  • Maintain Data Lake, Delta Lake, troubleshoot data source pipelines, handle scaling issues and be compliant with GDPR and Security. 
  • Responsible for anonymizing the data and creating test and training data for Machine Learning. 
  • Create and Maintain visual dashboards for data driven decisions.
  • 4+ years experience with data lake design and operations
  • 4+ years of experience with managing a high performance and highly scalable data pipelines
    • Deep experience with Spark, Hadoop on Cloud Storage and other ETL tools
  • 3+ years experience Scala, Java, Python, R programming 
  • 3+ years of experience with Scikit, TensorFlow Machine Learning frameworks
  • 1+ years of Query experience with technologies like Kafka, MySQL, ElasticSearch, BigTable and BigQuery 
  • 1+ year of experience with data transformation/preparation using apache beam, wrangler or any other open source technologies. 
  • Experience with enterprise cloud offering in Big Data Services, Data Store options and ML/AI offering
  • Colleagues describe you as self-driven, fast-learning, and hardworking
Preferred Qualifications
  • Google Cloud Platform Services - GCS, DataProc, Data Prep, Composer, AI Platform, BigQuery and Security features like IAM, Secret Manager
  • Hadoop/Presto/Delta Lake/Hive Setup and Maintenance
  • Familiarity with Tableau or Looker or DataStudio 
  • Interest/awareness with Jenkins or any CI/CD pipelines to maintain Data and ML pipelines.
  • Familiarity with container orchestration Kubernates

Compensation | Benefits

  • Competitive base salary
  • Full benefits package
  • Stock Options
  • Career growth with an industry innovator

BetterCloud is an Equal Opportunity Employer, including disabled and vets.


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We're in the heart of Chelsea where theres lots of great lunch and happy hour spots! Plus, the office is near tons of subways and Penn Station.
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