Data & AI Engineer

We are looking for an experienced Data & AI Engineer to join our team and contribute to enterprise and public-sector digital, data, cloud and AI platform engagements. The role focuses on building production-grade data products, AI-ready data pipelines and software services that ingest, transform, govern and serve both structured and unstructured data. You will apply strong software-engineering practices across data and AI delivery, including modular development, APIs, automated testing, CI/CD, observability, security and responsible use of AI-assisted coding tools. Key Responsibilities • Develop and maintain batch and real-time/streaming data ingestion and transformation pipelines. • Design and implement lakehouse architectures, curated data models, data products and serving APIs. • Implement data quality, metadata, lineage, classification and access-control mechanisms. • Build data pipelines supporting ML/AI use cases, document processing, embeddings, vector search and RAG solutions. • Develop modular, maintainable and production-ready solutions using Python, SQL and Apache Spark. • Implement automated testing, code reviews, CI/CD and deployment practices. • Work with cloud platforms, containers, orchestration and monitoring/observability tools. • Troubleshoot data and application issues and provide operational support for production workloads. • Use approved AI coding assistants such as GitHub Copilot, Microsoft Copilot or equivalent enterprise-approved tools to support development, testing, documentation and analysis. • Independently validate AI-generated code and ensure correctness, security, licensing compliance, performance and maintainability. • Collaborate with data scientists, software engineers, architects, business stakeholders and delivery teams. Required Skills & Experience • 5+ years of professional experience in data engineering, AI engineering, software engineering or a closely related field. • Strong hands-on experience with Python and SQL. • Experience developing ETL/ELT pipelines and data processing solutions. • Strong knowledge of Apache Spark and modern data/lakehouse architectures. • Experience with batch and streaming data processing. • Experience with APIs, Git, automated testing and CI/CD. • Exposure to cloud data platforms, containers, orchestration and observability. • Understanding of ML data preparation, embeddings, vector databases/search and Retrieval-Augmented Generation (RAG). • Understanding of data governance concepts including data quality, lineage, metadata and access control. • Experience working in complex enterprise or public-sector environments is highly desirable. • Demonstrated ability to independently review and validate AI-generated code. Education & Certifications • Bachelor's degree in Computer Science, Engineering, Information Systems or a related discipline. Preferred Certifications • Databricks Certified Data Engineer Associate • Microsoft Certified: Azure Data Engineer Associate • AWS Certified Data Engineer – Associate • Google Cloud Professional Data Engineer • Microsoft Certified: Azure AI Engineer Associate Preferred Technologies Experience with some of the following will be advantageous: Python | SQL | Apache Spark | Databricks | Azure/AWS/GCP | APIs | Git/GitHub | CI/CD | Docker | Kubernetes | Kafka | Airflow | Lakehouse | Vector Databases | RAG | LLMs | Data Governance | GitHub Copilot | Microsoft Copilot Show more Show less