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