Senior AI & Agentic Engineer – Expression of Interest (Future Opportunities)

Role overview

This posting is an Expression of Interest for future senior engineering opportunities focused on AI and agentic systems within a global data and analytics consulting environment. It is a resume-collection exercise rather than an immediate vacancy; the recruiting team may reach out as roles matching your experience open up. The work centers on designing scalable data platforms, leading engineering teams, and translating business needs into robust technical solutions.

Responsibilities

- Design, build, and maintain scalable data pipelines using SQL, Python, Databricks, Snowflake, Azure Data Factory, AWS Glue, Apache Airflow, and PySpark - Lead integration of complex data systems across multiple platforms, ensuring consistency and accuracy - Implement CI/CD practices to improve efficiency and quality of data processing - Partner with data architects, analysts, and stakeholders to translate business requirements into technical implementations - Manage and mentor a team of data engineers, providing guidance to ensure high-quality deliverables - Establish and enforce best practices in data governance, security, and compliance - Optimize data retrieval and develop dashboards and reports for business teams - Continuously evaluate emerging technologies to strengthen the engineering stack

Requirements

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field - 5–7 years of industry experience in data engineering with strong proficiency in SQL, Python, and big data technologies - Hands-on experience with cloud services such as Azure Data Factory and AWS Glue - Demonstrated experience with Databricks and Snowflake - Solid understanding of CI/CD principles and DevOps practices - Proven leadership and project management skills with the ability to run multiple projects in parallel - Excellent problem-solving skills and comfort working under tight deadlines - Strong understanding of data architecture including data mesh, data lake, and data warehouse

Nice to have

- Certifications in Azure, AWS, Databricks, Snowflake, or comparable technologies - Experience leading large-scale data engineering initiatives

Benefits and work setup

- Hybrid working model combining on-site collaboration with client-facing engagement and remote flexibility