We are looking for a
Lead Data & AI Engineer
to design and deliver data platforms and applications across a range of client engagements.
This role combines hands-on data engineering, technical leadership, and practical experience with AI, both in the solutions you build and in your daily development work.
You will work across different cloud platforms and technology stacks, helping teams build reliable data pipelines, well-governed data products, and AI-enabled applications.
Responsibilities
Lead the design and development of scalable data pipelines, platforms, and data products
Build batch and streaming solutions for ingestion, transformation, and delivery
Use AI coding assistants effectively in daily work to accelerate development, testing, debugging, and documentation, while reviewing and validating their output
Apply software engineering practices, including testing, code review, CI/CD, observability, and infrastructure automation
Design for data quality, security, governance, reliability, and performance
Contribute to AI applications, including data preparation, retrieval, integration, evaluation, and deployment
Help design and build agentic applications that use tools, APIs, and enterprise data to support business workflows
Make sound architectural choices across cloud services, processing frameworks, storage technologies, and orchestration tools
Work with clients and stakeholders to clarify requirements, explain trade-offs, and guide delivery
Mentor engineers and contribute to reusable patterns and engineering standards
Requirements
Strong experience in data engineering, including technical leadership on delivered projects




Hands-on programming skills in Python and strong SQL proficiency
Experience with distributed data processing, such as Apache Spark or equivalent technologies
Experience designing data pipelines and working with modern lakehouse, warehouse, or event-driven architectures
Practical experience with at least one major cloud platform: Azure, AWS, or Google Cloud
Experience with orchestration, automated deployment, testing, monitoring, and production support
Understanding of data governance, access control, and secure handling of enterprise data
Practical experience using AI development tools as part of an engineering workflow, with the ability to assess generated code for correctness, maintainability, and security
Experience developing AI applications, such as solutions using LLM APIs, retrieval-augmented generation, or AI-powered workflows
Working knowledge of agentic application patterns, including tool use, orchestration, state management, and evaluation
Robust communication skills and the ability to work directly with clients, architects, and delivery teams
Nice to have
Experience with Databricks, Snowflake, Microsoft Fabric, BigQuery, or similar platforms
Experience with Unity Catalog or other data governance tools
Experience with Terraform or other infrastructure as code tools
Experience building reusable frameworks or accelerators
Experience with streaming technologies such as Kafka
Experience with AI frameworks or platforms such as LangChain, LangGraph, Azure AI Foundry, Vertex AI, or Amazon Bedrock
Familiarity with AI application observability, guardrails, and responsible AI practices
Consulting or presales experience, including discovery workshops, solution design, and estimation

📌 Lead Data & Ai Engineer (Melbourne)
🏢 EPAM Systems
📍 Melbourne