High-Performance Data Architect

3 days ago

Sydney, New South Wales, Australia beBeeDataEngineer Full time $140,000 - $190,000

About Ticketek Entertainment Group

We are a global fan experience company that tickets, promotes and delivers live experiences impossible to forget. In a distracted world where nothing beats real human moments, we make life better live.

Our Fan Experience Platform sells tickets and provides value added services. We also promote events across Sport, Touring and Family Experiences. Our digital business focuses on delivering seamless data-driven outcomes for our fans and partners.

About the Role:

You will bring strong technical expertise in solution design, architecture, and coding to drive real outcomes in our data engineering initiatives. You will provide technical leadership, mentor junior engineers, and collaborate with Business and Product teams while continuously advancing your skills with the latest technologies and industry best practices.

Key Responsibilities:

  • Provide technical leadership in the data space, collaborating with cross-functional teams.
  • Act as a key driver of technical delivery, proactively identifying risks and solutions.
  • Lead technical solution design and troubleshooting, ensuring the team builds scalable and maintainable systems.
  • Ensure adherence to data privacy, security, observability, and governance standards.
  • Collaborate with architects and senior engineers to design resilient, high-performance data solutions.
  • Build scalable data pipelines to ingest, process, and expose data using technologies like Snowflake, AWS Redshift, Kinesis, Lambda, DynamoDB, S3, Glue, Apache Storm, and others.
  • Develop batch and streaming data solutions using Apache Kafka, Apache Spark, Airflow, and Delta Lake for real-time and scheduled data processing.
  • Design and implement event-driven data architectures with streaming frameworks such as Kafka Streams and Kinesis Data Firehose.
  • Implement Data Quality, Data Lineage, and Observability frameworks.
  • Build CI/CD pipelines using tools such as GitHub Actions, Terraform.
  • Collaborate with Site Reliability Engineers to ensure stability and uptime of production pipelines and services.
  • Continuously identify opportunities for performance improvement, cost optimisation, and process efficiency.
  • Work with Data Scientists to ensure high-quality data for Machine Learning models and integrate them into production-ready pipelines.

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