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April

Chief Data Architect

Macquarie Group Limited - Sydney, NSW

Any Industry
Source: uWorkin

JOB DESCRIPTION

We're looking for a candidate to fill this position in an exciting company.

  • work across a broad array of product heads, data scientists & business stakeholders to understand data needs across the full product lifecycle
  • ensure common understanding of our data and its quality, ownership and lineage throughout its lifecycle from capture through a client interaction through to reporting to internal and external stakeholders
  • provide guidance on solution architecture, engineering principles, and implementation of data applications using existing and emerging technology platforms
  • define the ownership, design and governance of fit-for-purpose logical and physical data domain models spanning data in motion and data at rest
  • build a strong data community through collaboration with other architects and engineers and work through this community to execute on opportunities to deliver better client and business outcomes through data
  • work as part of a global team of leading engineers and architects
  • have a high degree of flexibility in working arrangements, including physical location and time of day.
  • experience in end-to-end implementation of data intensive analytics-based projects (data acquisition, ingestion, integration, and transformation).
  • knowledge of design, development, and implementation experience utilizing data engineering technologies.
  • good understanding of AWS and GCP service landscapes, especially data services
  • experience building data ingestion on the cloud (for example using tools like Glue, Sqoop and vendor products like Talend, Unifi or StreamSets)
  • experience with big data technologies – AWS S3, Hive, noSQL/SQL databases (Redshift, Cassandra), parallel processing techniques, and Apache Spark
  • experience with data modelling techniques such as Data Vault and Kimball
  • understanding of streaming data architectures and technologies for real-time and low-latency data processing such as Kafka and Kinesis
  • familiarity with Agile methodologies, test-driven development, source control management, and automated testing
  • Financial Services / FinTech industry experience is not required.

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