Lead Data Engineer

Job Description

About Us

BOI is pioneering the field of AI strategy and applied AI, partnering with large-scale, ambitious businesses around the world to ideate, design, and build AI products that transform the way they work. We don’t just help organizations imagine what’s possible - we build the software that turns that vision into reality.

We work across different sectors and functions and have built a world-class team that unites commercial expertise, smart strategy, and technology. If you’re passionate about building enterprise AI products from 0->1 and leading projects at the forefront of AI innovation, we’d love to meet you!

About the Role

We are hiring a Lead Data Engineer to design, build, and manage scalable data pipelines that support our AI-powered tools and applications, including agentic tools that adapt to user behaviors. You will harmonize and transform data from disparate sources to ensure it is ready for use in foundational model integrations. The ideal candidate has prior experience in a consulting or agency environment and thrives in project-based settings.

This is a hands-on role where you will be responsible for building and implementing systems from the ground up. You would write production-level code while defining processes and best practices for future team growth.

Responsibilities

• Develop and manage ETL pipelines to extract, transform, and load data from various internal and external sources into harmonized datasets.
• Design, optimize, and maintain databases and data storage systems (e.g. PostgreSQL, MongoDB, Azure Data Lake, or AWS S3).
• Collaborate with AI Application Engineers to prepare data for use in foundational model workflows (e.g. embeddings and retrieval-augmented generation setups).
• Ensure data integrity, quality, and security across all pipelines and workflows.
• Monitor, debug, and optimize data pipelines for performance and reliability.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
• A minimum of 6 years of professional experience in data engineering.
• Proven experience working in a consulting or agency environment on project-based work.
• Experience in Python, SQL, and data transformation libraries like pandas or PySpark.
• Hands-on experience with data pipeline orchestration tools like Apache Airflow or Prefect.
• Solid understanding of database design and optimization for relational and non-relational databases.
• Familiarity with API integration for ingesting and processing data.
• Advanced English skills, both written and verbal, with the ability to communicate effectively in an international team.