Lead Data Engineer: AI & AWS Data Platforms

Deloitte Services

Sydney

On-site

AUD 180,000 - 280,000

Full time

14 days+

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Benefits offered by this job

Retail discounts

Wellbeing leave

Volunteer days

Flexible working options

Parental leave

Return to work support package

Job summary

Deloitte Services in Sydney seeks a Lead Data Engineer to spearhead AI & Data initiatives. You will own design and delivery of AI-enabled data platforms, guide teams, and ensure scalable, secure, and production-ready solutions for clients in Australia.

You will lead not only technical delivery but also mentoring and knowledge sharing, working with AWS services and data models while collaborating with clients to shape innovative data-driven outcomes.

Qualifications

4-6 years’ experience in software, data or AI engineering.
Strong software engineering background, with significant experience building data-intensive platforms
Strong Python engineering experience in production environments
Experience designing and building data models and data services for operational systems
Hands-on experience with AWS services such as DynamoDB, Aurora, Neptune and Glue
Experience with data ingestion, downstream consumption, semantic modelling, ontology design and lineage
Experience managing reference data and metadata-driven platform design
Experience curating or preparing high-quality datasets for testing, evaluation or operational controls
Experience working in complex distributed systems with strong quality and automation practices

Responsibilities

Designing & Delivering AI & Data Solutions – Design and deliver AI-enabled applications, agentic workflows and production-grade data solutions that are reliable, scalable, secure and maintainable.
Owning Technical Delivery – Apply AI-first delivery methods to lead the successful delivery of a workstream, making sound technical decisions and driving outcomes from design through deployment and operation.
Raising Engineering Quality – Review code and designs, champion engineering standards, and lift the quality of the solutions and teams around you.
Client Collaboration – Collaborate with client stakeholders and delivery teams to shape requirements, evaluate options and translate them into practical technical solutions.
AI-Enabled Delivery – Build in testing, CI/CD, observability, security and responsible AI practices from the start, using AI-first engineering methods to improve quality, consistency and delivery outcomes.
Coaching & Knowledge Sharing – Support the growth of less experienced engineers through mentoring, pairing, code review and sharing proven engineering patterns, practices and reusable assets.