Lead Domain Architect – Data (EL2)
- Department
- Architecture
- Location
- Canberra
- Workplace
- On-site
- Employment
- Contract
- Skills
The Lead Domain Architect – Data provides strategic architectural leadership for a specific business or technology domain. They develop and communicate domain architecture, ensure alignment with enterprise principles and business priorities, and guide complex solution designs. The role involves collaboration with architects, data engineers, stakeholders, and delivery teams, while advising senior executives and resolving multi-system architectural challenges.
More at Wattlecore Technologies
Related roles
Sydney Quantum Computing (SQC)
Data Analytics Engineering Lead
Engineering
The Data Analytics Engineering Lead will develop end-to-end data models and analytics capabilities to support the commercial strategy of a digital marketplace. Leading a team of analytics engineers, this senior role involves mentoring, setting technical standards, designing data architecture on platforms like DBT, Databricks, and Tableau, and working cross-functionally with product and marketing teams to enable self-service analytics.
- Quantum
Sydney Quantum Computing (SQC)
Canberra
Senior Solutions Architect, Public Sector
Engineering
In the position of Senior Solutions Architect for the Public Sector in Canberra, you will work closely with sales teams, partners, and clients to translate complex business needs into technical solutions using the Elastic Stack. Your day-to-day work includes system architecture design, technical advisory, and engaging with stakeholders to deliver scalable and secure solutions tailored to government and enterprise requirements.
- Quantum
Sydney Quantum Computing (SQC)
Solutions Architect - Data Science
Engineering
The Solutions Architect - Data Science position involves working directly with enterprise customers and partners to design and implement scalable AI and data science solutions using NVIDIA’s hardware and software platforms. The role includes providing technical guidance on generative AI, large language models, and AI frameworks, leading proof-of-concept projects, addressing complex technical challenges, and coordinating with internal teams to align customer needs with NVIDIA’s technologies. Strong engagement with developers, data scientists, and executives is required to drive adoption and optimize business processes through AI applications.
- Quantum