Analytics Platform Engineer Associate

Huron is redefining what a global consulting organization can be. Advancing new ideas every day to build even stronger clients, individuals and communities. We’re helping our clients find new ways to drive growth, enhance business performance and sustain leadership in the markets they serve. And, we’re developing strategies and implementing solutions that enable the transformative change they need to own their future.

As a member of the Huron corporate team, you’ll help to evolve our business model to stay ahead of market forces, industry trends and client needs. Our accounting, finance, human resources, IT, legal, marketing and facilities management professionals work collaboratively to support Huron’s collective strategies and enable real transformation to produce sustainable business results.

Join our team and create your future.

The Analytics Platform Engineer, Associate develops and maintains analytics infrastructure and deployment pipelines that enable teams across the organization to develop and deploy analytic products. This role focuses on implementing platform capabilities and supporting infrastructure development using cloud and data engineering technologies.

• Platform Infrastructure Development
  • Develops and maintains analytics infrastructure components and deployment pipelines.
  • Implements infrastructure‑as‑code solutions following established patterns.
  • Supports automated deployment processes for analytics products and data pipelines.
  • Contributes to platform scalability and reliability improvements.
  • Assists in ensuring platform performance meets team requirements.
• Data Pipeline Engineering
  • Builds and maintains ETL/ELT pipelines for data ingestion, transformation, and loading.
  • Develops data integration solutions connecting source systems to analytics platforms.
  • Implements data quality and validation processes within pipeline workflows.
  • Supports monitoring and alerting for data pipeline health and performance.
  • Assists in optimizing pipeline performance and resource utilization.
• Platform Services & Tools
  • Contributes to development of self‑service tools and platform capabilities.
  • Helps create standardized templates and patterns for analytics use cases.
  • Supports API and service development for platform integration.
  • Implements version control, testing, and deployment automation for platform components.
  • Assists in maintaining platform documentation and usage guidelines.
• Collaboration & Support
  • Partners with Product Owners, Data Scientists, and Analytics teams to understand platform needs.
  • Supports teams in adopting and leveraging platform tools and infrastructure.
  • Provides technical guidance on platform capabilities under supervision.
  • Gathers feedback from platform users to inform improvements.
  • Participates in agile ceremonies and contributes to platform roadmap discussions.
• Cloud & Dev Ops Practices
  • Implements cloud‑based analytics infrastructure using modern cloud platforms.
  • Applies Dev Ops and Data Ops principles to platform development.
  • Supports CI/CD pipelines for analytics infrastructure and data workflows.
  • Implements security, access control, and compliance measures in platform components.
  • Assists in monitoring platform performance and optimizing resource usage.
• Quality & Standards
  • Follows platform engineering standards and best practices.
  • Participates in code reviews and incorporates feedback.
  • Implements testing for platform components and data pipelines.
  • Documents technical designs and operational procedures.
  • Contributes to continuous improvement of platform capabilities.

• 2‑4 years of experience in platform engineering, software engineering, or data engineering.
• Proficiency in Python, SQL, and/or other relevant programming languages.
• Experience building cloud‑based data infrastructure (AWS, Azure, or Google Cloud Platform).
• Knowledge of ETL/ELT tools and frameworks (e.g., Airflow, dbt, Databricks, or similar).
• Understanding of infrastructure‑as‑code tools (Terraform, Cloud Formation, or similar).
• Familiarity with CI/CD tools and practices (Jenkins, Git Lab CI, Git Hub Actions, or similar).
• Knowledge of data warehousing concepts and analytics architectures.
• Good problem‑solving skills…