Lead Data Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Lead Data Engineer based in the United States.

The Lead Data Engineer will play a pivotal role in building and strengthening the data infrastructure that powers client reporting, business operations, analytics, and AI-driven solutions. This hands-on leadership position combines technical expertise with strategic decision-making, offering the opportunity to shape data architecture, guide platform development, and influence long-term technical priorities. You will collaborate with internal teams and external partners to build reliable, scalable, and well-governed data systems. The role also involves developing secure data foundations that enable AI tools to access and interpret information responsibly. As the data function grows, you will progressively take ownership of the platform and build a small team dedicated to data support and operational excellence. This is an opportunity to make a measurable business impact in a fast-paced, collaborative environment.

Accountabilities:

You will lead key aspects of data engineering, platform strategy, and team development, ensuring that data is reliable, secure, accessible, and useful across business functions. Working closely with senior leadership and cross-functional stakeholders, you will translate business needs into effective technical solutions while improving data quality and operational performance.

• Build, maintain, test, and document data pipelines and dbt models within Snowflake to ensure reliable, trusted data.

• Integrate data from paid media platforms, web analytics, SEO tools, CRM systems, and other business applications using ELT platforms such as Fivetran or Airbyte, alongside direct API integrations.

• Monitor data pipelines, investigate failures, resolve root causes, and proactively prevent disruptions before they affect internal teams or clients.

• Maintain data governance standards, including access controls, privacy safeguards, and consent requirements.

• Develop clear semantic layers, consistent metric definitions, and comprehensive metadata so AI agents can reliably interpret and use data.

• Design secure, governed access patterns for AI-powered tools, ensuring permissions are respected, queries remain appropriately scoped and read-only, and results can be traced to their sources.

• Partner with senior leadership to define data architecture, establish technical roadmaps, and evaluate build-versus-buy-versus-partner decisions.

• Translate business and client requirements into scalable data solutions, providing technical guidance and challenging requests when necessary.

• Ensure data models and governance frameworks support analysts, reporting systems, and AI-driven applications.

• Build and lead a small data support team responsible for Tier 1 and Tier 2 triage, including support playbooks, escalation procedures, and operational workflows.

• Expand the data team over time as business needs evolve, improving data accuracy, platform performance, and the tools available across the organization.

Requirements:

The ideal candidate brings extensive data engineering experience, strong technical ownership, and the ability to balance hands-on problem-solving with strategic planning. You should be comfortable working independently in an environment with ambiguity, communicating technical concepts clearly, and identifying practical solutions that meet broader business needs.

• At least 7 years of experience in data engineering or analytics engineering, including experience as a lead or senior technical owner of a production data platform.

• Extensive hands-on experience with Snowflake.

• Strong proficiency in dbt and advanced SQL, along with working knowledge of Python.

• Experience integrating SaaS platforms and marketing APIs, including advertising platforms, Google Analytics 4 (GA4), Salesforce, and HubSpot, through ELT tools and custom pipelines.

• Demonstrated ability to shape technical strategy, influence architecture decisions, and establish platform direction rather than simply execute assigned tasks.

• Strong troubleshooting skills, with the ability to diagnose complex pipeline issues, resolve root causes, and document solutions clearly.

• Excellent communication skills and the ability to collaborate effectively with both technical and non-technical stakeholders.

• A proactive, independent working style, with sound judgment and the ability to navigate ambiguity.

• Strong organizational skills and a practical, empathetic approach to understanding business requirements.

Preferred qualifications:

• Experience working with agency data or B2B marketing analytics.

• Knowledge of data governance and privacy practices, including role-based access controls, data masking, and consent management.

• Experience preparing data for AI- and large language model (LLM)-driven tools.

• Previous experience…