Data Engineer - Intelligent Forecasting at Dicks Sporting Goods in Pittsburgh, PA
At Dicks Sporting Goods, we are creating the future of sport driven by powerful data products and platforms that serve our Athletes and Teammates. We are looking for a Data Engineer who wants to be a part of a team solving the ingestion, enrichment, and activation of data to drive better development, forecasting, allocation, and insights into the products we sell. In this role, you will work with the core of how we use inventory, transaction, and historical forecast data working with modern cloud and open source technology to transform the future of sports. You would partner with Enterprise Analytics, Platform Services, and product development business teams to build the next generation of data insights. Work alongside data science teams building AI/ML models, platform engineers creating services that support you, and software developers creating unique experiences. This role builds new data products, pipelines, APIs, materialized views, services, and tools. The idea candidate is fascinated with data and the modern ways of creating rich, scalable data products driving how we work. What you will bring:
Experience and love for Python, Spark, SQL, or other standard data scripting languages Hands-on experience building, managing, and automating data pipelines Familiarity and appreciation for modern public cloud data services from AWS, GCP, or Azure 3
years of experience being close to the business and delivering value through it as part of a team. Some knowledge or exposure to supporting AI/ML engineering and integrating data to model development, management and serving. A good grip of data structures, relationships, integration patterns, and algorithms. You understand the importance of Kafka, Snowpipe, or Kinesis for real-time needs Some experience security and privacy to how you manage data. A grasp of the importance of common data platform patterns and how they relate like Data Lake, Data Mesh, Data Catalog, Tagging, Stream Processing, etc.
Salary Range:
$80K -- $100K
Minimum Qualification
Data Science & Machine Learning, Systems Architecture & EngineeringEstimated Salary: $20 to $28 per hour based on qualifications.
Experience and love for Python, Spark, SQL, or other standard data scripting languages Hands-on experience building, managing, and automating data pipelines Familiarity and appreciation for modern public cloud data services from AWS, GCP, or Azure 3
years of experience being close to the business and delivering value through it as part of a team. Some knowledge or exposure to supporting AI/ML engineering and integrating data to model development, management and serving. A good grip of data structures, relationships, integration patterns, and algorithms. You understand the importance of Kafka, Snowpipe, or Kinesis for real-time needs Some experience security and privacy to how you manage data. A grasp of the importance of common data platform patterns and how they relate like Data Lake, Data Mesh, Data Catalog, Tagging, Stream Processing, etc.
Salary Range:
$80K -- $100K
Minimum Qualification
Data Science & Machine Learning, Systems Architecture & EngineeringEstimated Salary: $20 to $28 per hour based on qualifications.
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