/n 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. /n 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/n /n

- Lead the design and development of scalable data pipelines, platforms, and data products

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- Build batch and streaming solutions for ingestion, transformation, and delivery

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- Use AI coding assistants effectively in daily work to accelerate development, testing, debugging, and documentation, while reviewing and validating their output

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- Apply software engineering practices, including testing, code review, CI/CD, observability, and infrastructure automation

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- Design for data quality, security, governance, reliability, and performance

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- Contribute to AI applications, including data preparation, retrieval, integration, evaluation, and deployment

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- Help design and build agentic applications that use tools, APIs, and enterprise data to support business workflows

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- Make sound architectural choices across cloud services, processing frameworks, storage technologies, and orchestration tools

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- Work with clients and stakeholders to clarify requirements, explain trade-offs, and guide delivery

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- Mentor engineers and contribute to reusable patterns and engineering standards

/n Requirements/n /n

- Strong experience in data engineering, including technical leadership on delivered projects

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- Hands-on programming skills in Python and strong SQL proficiency





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- Experience with distributed data processing, such as Apache Spark or equivalent technologies

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- Experience designing data pipelines and working with contemporary lakehouse, warehouse, or event-driven architectures

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- Practical experience with at least one major cloud platform: Azure, AWS, or Google Cloud

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- Experience with orchestration, automated deployment, testing, monitoring, and production support

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- Understanding of data governance, access control, and secure handling of enterprise data

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- Practical experience using AI development tools as part of an engineering workflow, with the ability to assess generated code for correctness, maintainability, and security

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- Experience developing AI applications, such as solutions using LLM APIs, retrieval-augmented generation, or AI-powered workflows

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- Working knowledge of agentic application patterns, including tool use, orchestration, state management, and evaluation

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- Strong communication skills and the ability to work directly with clients, architects, and delivery teams

/n Nice to have/n /n

- Experience with Databricks, Snowflake, Microsoft Fabric, BigQuery, or similar platforms

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- Experience with Unity Catalog or other data governance tools

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- Experience with Terraform or other infrastructure as code tools

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- Experience building reusable frameworks or accelerators

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- Experience with streaming technologies such as Kafka

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- Experience with AI frameworks or platforms such as LangChain, LangGraph, Azure AI Foundry, Vertex AI, or Amazon Bedrock

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- Familiarity with AI application observability, guardrails, and responsible AI practices

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- Consulting or presales experience, including discovery workshops, solution design, and estimation

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