Lead Data Engineer

About the Role
  
Our Client is seeking a Lead Data Engineer to take ownership of the design, development, and evolution of its data infrastructure. This is a highly influential technical role responsible for building scalable, reliable data systems that support the organization’s products, operations, and continued growth.
Working across engineering, product, and leadership teams, this individual will help shape the organization’s data architecture, technical standards, and engineering best practices. The ideal candidate is a hands-on technical leader who enjoys solving complex data challenges, building systems from the ground up, and operating with significant ownership in a fast-paced environment.
  
Key Responsibilities

• Architect, build, and scale data infrastructure supporting AI and product applications.
• Design and maintain data ingestion, transformation, storage, and processing architectures.
• Develop reliable batch and real-time data pipelines for large-scale operational workloads.
• Build and optimize vector search, retrieval, and machine learning data pipelines.
• Establish standards for data quality, security, governance, monitoring, and observability.
• Optimize large datasets, database performance, and query infrastructure.
• Partner with AI and backend engineers to support model training, inference, and product capabilities.
• Make key architectural and technology decisions that support scalability and long-term growth.
• Partner with product and executive leadership to translate data capabilities into product and business solutions.
• Establish engineering standards, best practices, and the foundation for a growing data engineering team.

Requirements

• 7+ years of relevant engineering experience, with a strong background in data engineering and architecture.
• Proven experience designing and scaling complex data pipelines, distributed systems, and data-intensive applications.
• Strong programming skills, particularly with languages commonly used in modern data engineering environments.
• Experience working across relational, non-relational, and modern data storage technologies.
• Familiarity with data processing, orchestration, messaging, search, and analytics frameworks.
• Strong understanding of data modeling, storage architecture, system performance, and optimization.
• Experience designing reliable, scalable data solutions within cloud-based environments.
• Ability to make sound architectural decisions and clearly communicate technical trade-offs to both technical and non-technical stakeholders.
• Exposure to machine learning, intelligent applications, streaming data, or event-driven architectures is advantageous.
• Comfortable taking significant technical ownership within a fast-paced, evolving organization.
• Strong problem-solving skills with a hands-on approach and experience building systems and processes from the ground up.