Lead Data Engineer

Harnham; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

Harnham is seeking a Lead Data Engineer to join its data engineering organization. This hands-on technical leader will design, build, and evolve scalable ELT pipelines powering customer-facing analytics.

This is not a pure management role; you will remain deeply technical while mentoring engineers, setting standards, and driving complex initiatives with a small data engineering team. The long-term view is to grow into formal people leadership as the organization expands, guiding others while

Qualifications

• 7–10+ years of overall engineering experience.
• Experience leading small engineering teams (≈3–8 people).
• Very strong SQL skills.
• Strong Python experience for data engineering and ELT.
• Experience designing and operating large-scale data ingestion and transformation pipelines.
• Experience with Airflow or a comparable orchestration framework.
• Ability to communicate tradeoffs clearly with stakeholders.

Responsibilities

• Serve as the senior technical leader within the Data Engineering organization.
• Design, build, and maintain scalable ELT pipelines powering customer analytics.
• Own data modeling, transformations, and onboarding of new data sources.
• Mentor engineers and establish engineering standards around reliability and observability.
• Lead complex initiatives from architecture through testing, deployment, and support.
• Collaborate with Product, Implementation, Customer Success, Analytics, and Engineering teams to resolve data issues.

Tools

dbt

Airflow

Job description

Work Authorization: U.S. Citizens or Green Card Holders. No sponsorship available.

About the Company

A growing SaaS company focused on analytics and workflow solutions is looking for a Lead Data Engineer to join its data engineering organization. The company works with complex datasets to deliver customer-facing analytics and data solutions that help organizations turn data into actionable insights.

This is an opportunity to join a growing engineering organization where the data engineering function has a direct impact on the customer experience and product.

About the Role

The Lead Data Engineer will be a hands-on technical leader responsible for designing, building, and evolving the data pipelines and architecture that power customer-facing analytics.

This is not a pure management role. The Lead Data Engineer will remain deeply technical while providing architectural direction, mentoring engineers, establishing engineering standards, and leading complex technical initiatives.

The ideal candidate is someone who can take ownership of ambiguous problems, understand an existing data environment, evaluate architectural tradeoffs, make thoughtful technical recommendations, and drive solutions from architecture through implementation.

What You'll Do

• Serve as the senior technical leader within the Data Engineering organization.
• Provide technical direction around architecture, data modeling, engineering practices, code quality, and complex problem-solving.
• Design, build, and maintain scalable and reliable ELT pipelines supporting customer-facing analytics.
• Own data modeling, transformations, and onboarding of new data sources.
• Lead complex initiatives from architecture and planning through implementation, testing, deployment, and ongoing support.
• Improve existing systems through automation, scalability, efficiency, reliability, and maintainability.
• Troubleshoot customer-facing data issues in partnership with Product, Implementation, Customer Success, Analytics, and Engineering teams.
• Establish engineering frameworks and standards around productivity, reliability, observability, and consistency.
• Contribute to the technical roadmap and identify opportunities to improve the broader data platform.
• Mentor and coach other data engineers.
• Evaluate architectural options, clearly communicate tradeoffs, and make technical recommendations.
• Help evolve existing data architecture thoughtfully rather than pursuing unnecessary rebuilds or greenfield solutions.

What We're Looking For

• 7–10+ years of overall engineering experience, with significant experience in Data Engineering.
• Experience leading or providing technical direction to small engineering teams, approximately 3–8 people.
• Very strong SQL skills.
• Strong Python experience, particularly for data engineering and ELT.
• Experience designing and operating large-scale data ingestion and transformation pipelines.
• Experience with Airflow or a comparable orchestration framework.
• Experience working with large datasets and varying data quality.
• Strong understanding of data architecture and architectural tradeoffs.
• Experience improving, modernizing, or migrating existing data architectures.
• Ability to think beyond individual pipelines and understand the broader data platform.
• Strong communication skills and the ability to work effectively with both technical and non-technical stakeholders.
• A strong technical point of view and the ability to explain why a particular technical approach is appropriate.

Nice to Have

• dbt
• Airflow/Astronomer, Dagster, or similar orchestration technologies
• Healthcare or health-related data experience
• Experience with financial services, advertising, transactional, or other complex data environments
• Experience troubleshooting customer-facing data issues

This position is initially structured as a Lead-level individual contributor role rather than a people-management position.

You will work alongside a small Data Engineering team and provide technical leadership, mentorship, architectural direction, and ownership of complex initiatives.

The long-term vision is to build a more traditional engineering growth structure, creating the potential for this person to move into formal people leadership and team management as the organization grows.

Candidates should therefore have demonstrated experience leading small teams or mentoring engineers and be interested in eventually taking on broader leadership responsibility.

The Right Mindset

The strongest candidate will be someone who can walk into an existing environment and say:

“Let me understand how this works, where the problems are, what our options are, and what I recommend.”

This is not a role for someone who wants to immediately rebuild an existing platform from scratch.

The company wants an engineer who can thoughtfully work within the current environment, troubleshoot and improve what exists, and identify when architectural changes or migrations actually make sense.

You should be comfortable balancing hands-on engineering with high-level architectural thinking and understanding how individual pipelines, data models, systems, and customer needs fit together.

Interview Process

• Hiring Manager / VP of Engineering Interview
• SQL Assessment
• Technical / System Design Conversation
• Culture Fit Interview

Compensation

The upper end of the range is reserved for candidates who demonstrate exceptional depth across data engineering, architecture, technical leadership, and the other core requirements of the role.