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.
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- Country
- United States of America
