This employer will not sponsor applicants for employment visa status (e.g., H1-B) for this position. All applicants must be currently authorized to work in the United States on a full-time basis.

Role Summary

The Director of Integration Engineering leads Loopbacks Data Integration team and serves as the senior-most authority on integration engineering. Reporting directly to the CTO, this role is accountable for the execution of integrations with a focus on speed, predictability, quality, and cost efficiency. The Director is a hands-on technical leader reviewing code, mentoring engineers, and instilling engineering best practices while driving outcomes at scale through automation, frameworks, and process discipline.

This role owns Loopbacks speed-to-value and unit economics for integrations, including both labor and infrastructure costs. The Director ensures new data sources are onboarded rapidly, accurately, and cost-effectively, with measurable impact on platform economics and client delivery outcomes.

Key Responsibilities

• Integration Leadership: Lead and grow the Data Integration team (data analysts and engineers) with a focus on speed, quality, and predictability.
• Technical Oversight: Provide hands-on review of Python, SQL, and Databricks code, ensuring technical excellence and maintainability.
• Mentorship: Elevate team capability through structured coaching, code reviews, and setting engineering best practices.
• Process Discipline: Define and enforce integration playbooks, onboarding frameworks, and delivery practices that reduce cycle times and defects.
• Cross-Functional Partnership: Collaborate with Product, Data Engineering, RWD, and PMO to align integration outcomes with business priorities and client expectations.
• Unit Economics & Cost Discipline: Own and track the economic performance of integrations, including cost-per-implementation, infrastructure costs, and opportunity cost of schedule delays translating integration economics into actionable engineering decisions and strategies for leveraging labor alternatives.
• Automation & Innovation: Drive initiatives that reduce manual effort in onboarding, optimize Snowflake/Databricks infrastructure spend, and improve speed-to-value.
• Domain Expertise: Apply deep healthcare data knowledge (Epic, Cerner, pharmacy, claims, RWD) to accelerate mapping, normalization, and onboarding success.

Qualifications & Profile

• Strong technical background in Python, SQL, Databricks, and/or Snowflake, with the ability to evaluate and guide code at depth.
• Proven success leading integration or data engineering teams, with a record of mentoring and multiplying the impact of others.
• Demonstrated success in healthcare data environments Epic or Cerner integration experience strongly preferred.
• Strong understanding of data onboarding, mapping, and normalization processes.
• Experience in defining, tracking, and improving unit economics for technical delivery and infrastructure costs.
• Effective cross-functional collaborator with Product, Data Engineering, PMO, and business stakeholders.
• Balance of strategic mindset with willingness to get hands dirty in technical review and process definition.

Success Metrics

• Cycle Time: Demonstrated reduction in onboarding duration, accelerating speed-to-value.
• Quality: High first-pass acceptance of integrations with minimal rework required.
• Predictability: Reliable delivery of integrations on committed schedules.
• Automation & Frameworks: Increased leverage of automation and reusable patterns in integration delivery.
• Cost Efficiency: Measurable reduction in both labor and infrastructure costs per integration.
• Unit Economics: Defined, tracked, and continuously improved economics across integration types, incorporating cost-per-integration, opportunity cost of delay, and strategies for leveraging labor alternatives.
• Client Impact: Measurable improvement in client confidence and satisfaction with Loopbacks delivery performance.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, or national origin.