Senior Data Architect

2 weeks ago

Melbourne, Victoria, Australia beBeeDataEngineer Full time $180,000 - $210,000
Job Description

As a senior data engineer, you will play a crucial role in architecting and evolving core components of the data ingestion platform. Your expertise will shape how data flows across domains at enterprise scale.

The ideal candidate will combine deep systems thinking with hands-on development and mentorship skills. You will lead the development of end-to-end ingestion systems, including source integration transformation logic and pipeline orchestration.

Required Skills and Qualifications
  • 7+ years of experience as a software or data engineer with a focus on building distributed systems and high-scale ingestion platforms.
  • Deep fluency in software engineering principles, data structures, concurrency, fault-tolerant design, testability, and performance optimization.
  • Proven experience leading the development of end-to-end ingestion systems, including source integration transformation logic and pipeline orchestration.
  • Strong understanding of data contracts, schema evolution, and lineage as foundational elements of trusted reusable data.
  • Familiarity with large-scale data environments, cloud-native columnar stores, streaming architectures, and the tradeoffs in latency, cost, and throughput.
  • Ability to influence platform direction through architecture reviews, RFCs, and mentorship not just individual contributions.
  • A product-minded engineering perspective able to balance technical rigor with pragmatic delivery for real-world impact.
Benefits

This is an opportunity to help shape how WEX ingests and leverages its most valuable asset: data. If you're passionate about scaling data platforms from the ground up, this is your chance to make a significant impact.

You will be working closely with cross-functional stakeholders to align ingestion strategies with domain modeling, analytics, and product delivery goals.

Others

Key responsibilities include architecting and evolving high-performance data acquisition pipelines, designing and implementing reusable platform components, and optimizing ingestion for both batch and streaming flows.

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