Remote Remote - Manager Data Engineering and Analytics - Ecommerce

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About the Role:

We're looking for an Engineering Manager to join the CrowdStrike Digital Commerce Data and Decisions team. This dynamic leader will be covering data and data analysis for the CrowdStrike App Store and ecosystem, product and service monetization (in-app purchasing/micro-transactions/etc), Licensing, Billing, Entitlement and Consumption across the entire product portfolio, and all the backend analytics work to drive a better user experience and optimize engagement, conversion, cross-sell and up-sell, minimize risk and fight fraud.

We are looking for a technical lead and engineering manager with experience leading a data and/or analytics engineering team and mentoring developing engineers. We leverage technologies like Apache Kafka, Cassandra, and Spark; we deploy and run solutions on multi-cloud (AWS, GCP, and in our own data centers); and we run on top of a system that strips any hyperbole from the term “big data” – processing over a trillion events daily.

What You’ll Need:

  • 2-5 years of tech lead or engineering manager experience with cloud or data engineering teams.

  • Proficiency in agile/scrum frameworks with experience leading scrum teams.

  • Clear communication, proactive planning and risk management toward team goals.

  • Experience developing and mentoring engineering staff

  • A solid understanding of algorithms, distributed systems design and the software development lifecycle

  • Background in Java/Scala or scripting languages like Python

  • Experience building and operating large scale production data pipelines

  • A passion for data solutions and willingness to pick up new programming languages, technologies, and frameworks

What Your Team Will Do:

  • Work in the Apache Hadoop ecosystem including: Spark, Kafka, Hive, etc.

  • Relational SQL and NoSQL databases, including Postgres/MySQL, Cassandra, DynamoDB

  • Custom ETL design, implementation and maintenance.

  • Schema design and dimensional data modeling.

  • Data Analysis, User and Product Analytics, Data Insights

  • Decision Science and Predictive Analytics systems to reduce risk, fight fraud, increase engagement and optimize conversion and cross-sell opportunities

  • Analyze data to identify deliverables, gaps and inconsistencies.

  • Manage and communicate data warehouse plans to internal clients.

  • CI/CD processes and source control tools such as GitHub and related dev processes





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