Lead Data Engineer at V2 Digital

Sydney, New South Wales, Australia -

Full Time

Start Date

Immediate

Expiry Date

11 Jun, 26

Salary

0.0

Posted On

13 Mar, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Databricks, Spark, Lakehouse Architecture, AWS, Azure, GCP, Data Pipelines, Cloud Data Platforms, Data Modelling, Data Architecture, Machine Learning, AI, Data Engineering, Orchestration, Data Quality, Distributed Data Processing

Industry

IT Services and IT Consulting

Description

About V2 AI V2 AI is a leading AI-Native consultancy backed by $30m in VC funding, allowing us to meet our customers' needs. We harness the power of AI to accelerate business outcomes for some of the world's largest brands. We bring decades of experience and a unique delivery model to partner with our customers on the most complex problems for immense, measurable impact. Our Services AI Strategy & Governance AI Enablement Applied AI Data & AI Security About the Role As a Lead Data Engineer (Databricks), you'll drive the design and development of modern data platforms and scalable data pipelines. You'll lead data engineering initiatives using Databricks and lakehouse architecture, building robust data pipelines and deploying scalable cloud data platforms across AWS, Azure, or GCP. You'll collaborate with product teams, architects, AI engineers, and other data engineers to deliver end-to-end data solutions, including modern data platforms, advanced analytics capabilities, and data foundations that enable machine learning and AI applications. You'll also mentor team members, influence technical decisions, and help shape data engineering standards and practices across V2 AI. Responsibilities: Lead the design, development, and deployment of data platforms and pipelines using Databricks, Spark, and cloud technologies Build and optimise batch and streaming data pipelines to support analytics, machine learning, and AI workloads Collaborate with cross-functional teams (product, data, AI, and architecture) to define data models, platform architecture, and technical strategy Ensure scalable, secure, and maintainable cloud data architectures leveraging AWS, Azure, or GCP services Mentor and guide engineers on data engineering best practices, code quality, and architectural decisions Implement data platform workflows, including orchestration, monitoring, data quality, and performance optimisation Work with structured and unstructured data to enable advanced analytics and AI-driven capabilities Contribute to reusable data frameworks, pipelines, and engineering standards Stay up to date with modern data engineering technologies, Databricks capabilities, and cloud data platforms, sharing knowledge internally and externally About You: Extensive experience designing and delivering data engineering solutions and modern data platforms Strong expertise with Databricks, Spark, and lakehouse architecture Experience building scalable data pipelines and distributed data processing systems Experience working with modern data platforms such as Databricks, Snowflake, or similar ecosystems Strong cloud experience across AWS, Azure, or GCP Deep understanding of data modelling, data architecture, and data engineering best practices Experience mentoring engineers and influencing technical decisions across projects Passionate about building scalable data platforms, reusable frameworks, and high-quality engineering solutions Excellent communicator and collaborator, able to work across engineering, product, and data teams Benefits: Competitive Salary package Pick your equipment Gifted Day Off ("VersionUp Day") Generous parental leave Well funded start up $$$ Annual Training budget Mentorship Program Clear promotion pathways Flexible working Meet-ups & socials 97% Rating on corporate social responsibility APPLY NOW: If you are keen to join one of the fastest-growing consultancies in this space and interested in shaping the future of V2 AI, then APPLY NOW!

Responsibilities

The Lead Data Engineer will drive the design, development, and deployment of modern data platforms and scalable data pipelines, primarily utilizing Databricks and lakehouse architecture across major cloud providers. This role involves collaborating with cross-functional teams to deliver end-to-end data solutions while mentoring team members and shaping engineering standards.