Data Engineer – Python, Azure, Sports Data

5 days ago

Melbourne, Victoria, Australia XO Sports Full time $90,000 - $120,000 per year

About XO Sports

XO Sports is building a next-gen B2C mobile platform for the online sports market, starting with the NBA and expanding into AFL, NRL, and NFL over the next 12 months. Our platform is powered by Azure cloud, leveraging a broad range of data services including Data Factory, Databricks, ADLS Gen2 and github to enabling us to ingest, transform data model for ML training.  These insights can then be published real-time insights to fans and punters.

Role Summary

We're looking for hands-on Data Engineers 2 years experience to join our growing backend team. You'll be responsible for building and maintaining the data pipelines that power our machine learning models and mobile app. This is a great opportunity to work with modern data tools, solve real-world data problems, and help shape the future of sports analytics.

What You'll Be Doing

  • Build and maintain data pipelines for ingesting NBA data from external APIs, using Azure Data Factory

  • Transform ingested raw JSONL data into structured formats using Python notebooks (pandas/dataframes) publishing to Databricks DeltaTables across a medallion architecture

  • Design and manage dimension tables (SCD2) and development of surrogate keys for linking common external datasets for pipeline redundancy

  • Ensure data quality through testing and validation of transformation logic.

  • Collaborate with data scientists and developers to support ML model development through engineering of features

  • Work within the Azure ecosystem, including, but not limited to, Data Factory, Databricks, ADLSv2, Azure Queues, Function Apps afnd CosmosDB

  • Use GitHub for version control and collaborate in an Agile environment using Jira.

What You Bring

You're a problem-solver who enjoys working with data at scale, writing clean Python code, and building systems that are reliable and scalable.

Must-haves:

  • Strong Python skills, especially for data transformation using pandas/dataframes.

  • Experience designing and maintaining dimension tables (SCD2).

  • Ability to develop and manage surrogate keys for data linking.

  • Experience testing and validating data pipelines to ensure accuracy and integrity.

  • Ability to conceptualize and design solutions to complex data transformation problems.

Nice-to-haves:

  • Familiarity with the Databricks ecosystem, including Unity Catalog, Delta Tables, and Medallion architecture.

  • Experience with Azure Data Factory and cloud-based data ingestion.

  • Interest in sports (NBA, AFL, NRL, NFL, soccer) and understanding of sports statistics.

  • Experience using GitHub for code management and collaboration.

Why Join XO Sports?

  • Work on a greenfield project with modern tools and real-world impact.

  • Help shape the data backbone of a cutting-edge sports tech platform.

  • Join a passionate, fast-moving team with a clear product vision.

  • Flexible work setup – remote, hybrid, or in-office.

  • Competitive salary + equity options.

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