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 AssociateMicrosoft Certified: Azure Data Engineer AssociateAWS Certified Data Engineer – AssociateGoogle Cloud Professional Data EngineerMicrosoft 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