Lead data platform engineer (manager / architect)

Huron helps its clients drive growth, enhance performance and sustain leadership in the markets they serve. We help healthcare organizations build innovation capabilities and accelerate key growth initiatives, enabling organizations to own the future, instead of being disrupted by it. Together, we empower clients to create sustainable growth, optimize internal processes and deliver better consumer outcomes.

Health systems, hospitals and medical clinics are under immense pressure to improve clinical outcomes and reduce the cost of providing patient care. Investing in new partnerships, clinical services and technology is not enough to create meaningful and substantive change. To succeed long-term, healthcare organizations must empower leaders, clinicians, employees, affiliates and communities to build cultures that foster innovation to achieve the best outcomes for patients.

Joining the Huron team means you’ll help our clients evolve and adapt to the rapidly changing healthcare environment and optimize existing business operations, improve clinical outcomes, create a more consumer-centric healthcare experience, and drive physician, patient and employee engagement across the enterprise.

Join our team as the expert you are now and create your future.

We are looking for a Lead Data Engineer to provide technical leadership for our engineering team and take on one of our most strategically important challenges: unifying a diverse ecosystem of analytics applications under a coherent, scalable technology platform.

Our analytics landscape has grown organically across multiple teams and products. The result is a collection of powerful but siloed tools, each with its own technology stack, data contracts, and deployment patterns. You'll join a team that acts as the connective tissue bringing these applications together, making pragmatic decisions about when to consolidate and when to preserve the right tool for the right job.

This role is for an engineer who is energized by ambiguity, skilled at reading distributed systems, and opinionated (but flexible) about platform design. You will work directly with engineering leads and data teams. As the team's technical lead, you will guide and mentor other engineers while remaining a hands-on contributor.

What You'll Do

Technical Leadership

• Set technical direction for a small team of platform engineers, translating requirements and architecture guidance into well-scoped, sequenced work
• Mentor engineers through pairing, code review, and design feedback, raising the team's standards for quality, testing, and documentation
• Coordinate delivery across contributors, including distributed team members, surfacing risks and dependencies early
• Remain a primary hands-on contributor to the team's most complex integration and platform work

Platform Unification & Integration

• Audit existing analytics applications to understand their underlying technology choices, data flows, and integration points
• Design and implement integration patterns (APIs, event streams, shared data contracts) that allow siloed applications to interoperate without unnecessary rewrites
• Build and maintain shared platform services (authentication, observability, configuration management, logging) that reduce duplication across applications

Data Pipeline & ETL Engineering

• Develop a deep understanding of existing data pipelines owned by distributed teams, including their data sources, transformation logic, and dependencies
• Partner with domain teams who have the deepest knowledge of their own data, acting as an integration architect and collaborator rather than a centralized pipeline owner; identify unification opportunities but defer to domain expertise on data semantics and processing logic

Cloud Infrastructure

• Deploy and manage platform services on cloud infrastructure (AWS preferred; Azure/GCP experience a plus)
• Contribute to infrastructure-as-code practices using tools such as Terraform or CDK
• Collaborate with the IT platform team to define deployment pipelines and reliability standards for integration services
• Construct evidence-based business cases for cloud feature adoption, translating technical requirements into business value, risk reduction, and compliance language that resonates with IT governance and procurement stakeholders

What We're Looking For

Required Qualifications

• 7+ years of software engineering experience, with at least 3 years focused on data engineering, integration, platform, or infrastructure work
• 2+ years in a technical lead role: setting direction for shared work, mentoring engineers, and reviewing code and designs
• Proficiency in Python; comfortable reading and writing production-quality code, not just scripts
• Strong SQL skills, including working with large or complex datasets
• Hands-on experience with AWS (compute, storage, and at least one managed data service)
• Experience with AI-assisted development tools or coding agents in a professional context, and a genuine curiosity about how AI is changing engineering work
• Demonstrated ability to learn unfamiliar systems quickly: you can walk into an existing pipeline, tool, or codebase you didn't build and figure out how it works
• Strong written communication skills

Preferred Qualifications

• Experience with dbt and Snowflake
• Experience with Apache Iceberg
• Additional language proficiency, especially Spark or Java
• Experience leading or coordinating engineering work across distributed or multi-location teams
• Experience with data pipelines (ETL/ELT), including schema management or data quality monitoring
• Exposure to structured (SQL) and semi-structured (JSON, Parquet, Avro) data at scale
• Familiarity with analytics or ML platform tooling (Airflow, MLflow, or SaaS equivalents)

How You Work

We care as much about how you think as what you've built. The ideal candidate for this role:

• Is pragmatic over dogmatic: comfortable making a clear recommendation and defending it, but changes course when someone presents a genuinely better argument, not just a louder one
• Treats AI-assisted tools as a normal part of how you work, not a novelty, and stays curious about how they change what's possible
• Communicates tradeoffs clearly to both technical peers and non-technical stakeholders
• Moves quickly from “I don't know this system” to “here's how it works,” and can produce a clear map of an unfamiliar codebase or pipeline
• Understands that “don't touch what works” and “build it right” are often both correct answers, depending on context
• Takes ownership of quality and reliability: you care about what happens after you ship
• Multiplies the team's impact: shares context, unblocks others, and delegates real ownership rather than becoming the bottleneck

The estimated base salary for this job is $140,000 - $190,000 USD. The range represents a good faith estimate of the range that Huron reasonably expects to pay for this job at the time of the job posting. The actual salary paid to an individual will vary based on multiple factors, including but not limited to specific skills or certifications, years of experience, market changes, and required travel. This job is also eligible to participate in Huron’s annual incentive compensation program, which reflects Huron’s pay for performance philosophy. Inclusive of annual incentive compensation opportunity, the total estimated compensation range for this job is $168,000 - $228,000 USD. The job is also eligible to participate in Huron’s benefit plans which include medical, dental and vision coverage and other wellness programs. The salary range information provided is in accordance with applicable state and local laws regarding salary transparency that are currently in effect and may be implemented in the future.