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Analytics Engineer

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At PrizePicks, we are the fastest growing sports company in North America, as recognized by Inc. 5000. As the leading platform for Daily Fantasy Sports, we cover a diverse range of sports leagues, including the NFL, NBA, and Esports titles like League of Legends and CS:GO. Our team of over 350 employees thrives in an inclusive culture that values individuals from diverse backgrounds, regardless of their level of sports fandom. Ready to reimagine the DFS industry together?

The Analytics Team is responsible for building and maintaining analytics tools and workflows to support the PrizePicks business across all departments — at the core of these operations is data. As an Analytics Engineer, you are passionate about distilling disparate data into highly visible and actionable insights and helping build a world-class Analytics organization. By developing, maintaining, and testing data generation infrastructures, you will enable the PrizePicks to make smarter, better, and faster data-driven decisions.

What you’ll do:

  • Create and maintain optimal data pipeline architecture, ensuring data reliability in operationalized data sets.
  • Expand our data lake with clean, reliable, and timely data ready for analysis.
  • Define and improve our internal standards for data format, maintainability, observability, and best practices for a rapidly scaling data infrastructure.

What you have:

  • Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
  • Strong analytic skills related to working with unstructured datasets.
  • Experience building and optimizing ETL/ELT ‘big data’ pipelines, architectures, and data sets.
  • Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
  • Experience building data visualizations and dashboards for internal/external stakeholder communication and insights
  • 2+ years of experience in a data analytics or data engineering role
  • A graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field.
  • Experience using the following software/tools:
  • Data Ingestion tools: Hevo, Fivetran, Stitch, etc.
  • Relational SQL databases/warehouses: Postgres, BigQuery.
  • Object-oriented/object function scripting languages: Python.
  • Data modeling tools: dbt Cloud and Core.
  • Cloud platform services in GCP and analogous systems: BigQuery, BigTable, Cloud Storage, Cloud Compute Engine, Looker, DataStudio, CloudSQL.
  • Dashboarding platforms: Tableau, Looker, etc
  • Code version control: Git
  • Preferred experience with data observability/freshness/lineage tools: Elementary
  • Preferred experience with big data tools: Dataproc, Hadoop, Spark,, etc.
  • Preferred experience with data pipeline and workflow tools: Prefect, Airflow, Cloud Composer, Azkaban, Luigi, etc.

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