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Sr. Analytics Engineer

Simplebet LogoSimplebet
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Our mission is to power the future of fan engagement.

Simplebet is a B2B sports technology company that uses machine learning and real-time solutions to make every moment of every sporting event a betting opportunity. We’re reimagining how people enjoy sports with products that are simple, intuitive, and entertaining.  Our technology powers micro-betting capabilities of the leading operators around the globe.

We are looking to hire a Senior Analytics Engineer to join the Simplebet Data Engineering Team to contribute to our data platform. This includes building ETL pipelines, Django web applications, relational databases, and streaming real time data into analytics applications and data lake. You will be responsible for fetching, organizing, manipulating, and maintaining all of our data in order to optimize machine learning research, product analytics, and streaming data products for our machine learning and customer use cases.

  • Build robust and reliable ETL pipelines using Python, SQL, Prefect, Databricks, dbT, Kafka, and PostgreSQL
  • Organize raw sports data from a variety of sources into a cohesive, centralized data warehouse
  • Build and improve our real-time streaming data infrastructure and products
  • Work closely with the product analytics team to supply tools for supporting data analytics
  • Help manage and build BI infrastructure
  • Conduct adhoc data analysis for performance monitoring, data quality anomaly detection, and business efficiency
  • Participate in modern workflows such as source code and code reviews
  • Build and optimize the performance of data pipelines and analytical tools for scale
  • Foster innovation with emerging technologies and by staying current with industry trends
  • Guide professional development of the team through technical leadership
  • Partner with stakeholders to solve business problems with technical solutions
  • Maintain detailed documentation of data pipelines, processes, and best practices

Requirements

  • 4+ years of data-oriented software development experience
  • Proficiency with SQL and Python
  • Strong understanding of database and Data Lake design
  • Experience building and maintaining web services in production using a modern framework like Django, Flask, or FastAPI
  • Experience with a message broker or data streaming technology such as RabbitMQ or Kafka
  • Experience deploying applications into a Kubernetes environment
  • Experience utilizing version control tools such as GitHub
  • A DevOps mindset characterized by automation, collaboration, continuous improvement, and a hyperfocus on user needs and frequent iteration
  • Strong communication skills and ability to distill technical solutions into business terms
  • Creative problem-solving abilities to embrace and navigate ambiguity and change
  • Insatiable curiosity and interest in learning new things

Bonus Points For

  • Experience working with Databricks, Prefect, Spark, Celery, and/or Tableau
  • Experience with ML Classification models
  • Experience with a monitoring/observability tool stack such as ELK, Datadog, Splunk, etc
  • Experience supporting Data Science / Machine Learning teams
  • Knowledge of and passion for sports

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