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 Git Hub 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/Git Hub | CI/CD | Docker | Kubernetes | Kafka | Airflow | Lakehouse | Vector Databases | RAG | LLMs | Data Governance | Git Hub Copilot | Microsoft Copilot #J-18808-Ljbffr