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 Strong 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
