Job description

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 Platform Integration Engineer to join 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 will be the connective tissue that brings 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, and you will be empowered to use AI-assisted development tools as a first-class part of your workflow. What You’ll Do 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 Evaluate build vs. consolidate vs. federate tradeoffs for components across the platform, documenting your rationale and driving alignment 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 Design and build a unified presentation layer that surfaces data from heterogeneous compute environments — including large-scale distributed systems (e.g., Spark) and traditional relational databases — in a consistent, accessible way 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, CDK, or Pulumi Collaborate with DevOps/SRE 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 3 years of software engineering experience, with at least 1 years focused on integration, platform, or infrastructure work Proficiency in at least one backend language commonly used in data-intensive systems (Python, Go, Java, or similar); proficiency in two or more languages strongly preferred Hands-on experience with cloud platforms (AWS strongly preferred) including compute , storage, networking, and managed services Experience building and operating data pipelines (ETL/ELT), including schema management and data quality monitoring Working experience with AI-assisted development tooling in a professional engineering context Strong written communication skills — able to produce clear architecture decision records (ADRs), runbooks, and design documents Preferred Qualifications Experience evaluating and rationalizing heterogeneous technology stacks — i.e., inheriting systems you didn’t design and making them work together Familiarity with analytics or ML platform tooling (e.g., Airflow, dbt , MLflow , Spark, or SaaS equivalents) Experience with API gateway management, service mesh, or distributed tracing tooling Background working with both structured (SQL) and semi-structured (JSON, Parquet, Avro) data at scale 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 — you reach for the right solution given real constraints, not the theoretically perfect one Communicates tradeoffs clearly to both technical peers and non-technical stakeholders Is comfortable making a recommendation and defending it, but genuinely updates when presented with better information Brings structure to ambiguous problems — you can walk into a complex legacy system and produce a clear map of what’s there 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 What We Offer Competitive base salary commensurate with experience Flexible remote-first or hybrid work environment Opportunity to define integration and platform patterns that will shape the organization’s technical direction The estimated base salary for this job is $100,000 - $130,000 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 $112,000 - $153,400 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. #LI-CL1 #LI-Remote Position Level Associate Country United States of America

Requirements

Must-haves

Join our team as the expert you are now and create your future.
What You’ll Do
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
Evaluate build vs. consolidate vs. federate tradeoffs for components across the platform, documenting your rationale and driving alignment
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
Cloud Infrastructure
Contribute to infrastructure-as-code practices using tools such as Terraform, CDK, or Pulumi
Collaborate with DevOps/SRE to define deployment pipelines and reliability standards for integration services

Nice-to-haves

Deploy and manage platform services on cloud infrastructure (AWS preferred; Azure/GCP experience a plus)
Proficiency in at least one backend language commonly used in data-intensive systems (Python, Go, Java, or similar); proficiency in two or more languages strongly preferred
Hands-on experience with cloud platforms (AWS strongly preferred) including compute , storage, networking, and managed services
Experience evaluating and rationalizing heterogeneous technology stacks — i.e., inheriting systems you didn’t design and making them work together
Familiarity with analytics or ML platform tooling (e.g., Airflow, dbt , MLflow , Spark, or SaaS equivalents)
Experience with API gateway management, service mesh, or distributed tracing tooling
Background working with both structured (SQL) and semi-structured (JSON, Parquet, Avro) data at scale
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 — you reach for the right solution given real constraints, not the theoretically perfect one
Communicates tradeoffs clearly to both technical peers and non-technical stakeholders
Is comfortable making a recommendation and defending it, but genuinely updates when presented with better information

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

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Platform: workday
Effort: long

Benefits

Benefits detected in the listing.

Dental

Vision

Wellness