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Technical Product Analyst

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Remote from
USA
Salary
USD 85k–105k / yr
Employment
Full Time
Experience
Open level
Published
Apply before
24 Oct 2026
Listing views
1,009
Application actions
75
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AI Summary

The role, at a glance.

CentralReach seeks a Technical Product Analyst to support Data Product teams by translating requirements into validated, production-ready analytics and data products. The role centers on SQL-based source-to-target validation, metric reconciliation, dashboard quality assurance, regression testing, and investigation of production data discrepancies. This analyst will partner with Product Managers and Engineering while serving as a front-line resource for dashboard and data questions from internal and external stakeholders. Success requires strong BI reporting experience, Agile product-delivery familiarity, disciplined documentation, and the ability to improve and automate recurring data-quality checks.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

4/5
EasyHard

Pace & Pressure

4/5
RelaxedFast-paced

Autonomy Level

4/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThe position requires independent resolution of ambiguous data-logic issues across source systems, transformation layers, and BI dashboards. It also combines technical validation work with product collaboration, stakeholder support, release-cycle coordination, and process automation.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)
$95,000
US market range (period not specified)$80k–$115k
AI insightSalary comparison is unavailable: the pay periods are unspecified or differ, or salary amounts are unavailable. Market figures are AI estimates. Regenerate the analysis to obtain a market estimate with an explicit period.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you validate that a dashboard metric accurately reflects source-system data?

I would first define the metric's business logic and grain, then trace its lineage from source tables through transformations to the BI semantic layer. I would use SQL to reconcile record counts, joins, filters, aggregations, and edge cases, documenting variances and confirming expected behavior with the Product Manager and Engineering team.

Describe how you would investigate a reported discrepancy in a production dashboard.

I would reproduce the issue using the reported filters, user permissions, and time period, then compare the dashboard output with underlying query results and source data. I would isolate whether the problem stems from ingestion, transformation logic, the elasticube or semantic layer, dashboard configuration, or user interpretation, and communicate the evidence and recommended owner clearly.

What makes an effective data-validation test case?

An effective test case has a clear objective, defined inputs, expected outputs, data lineage assumptions, and reproducible SQL or steps. It should include normal cases, boundary conditions, null or duplicate scenarios, and known business exceptions so that it can be reused during regression testing.

How would you prioritize incoming stakeholder questions alongside release-readiness work?

I would triage requests based on production impact, affected users, data integrity risk, release deadlines, and effort to resolve. Critical issues affecting decision-making or broad customer groups would be addressed first, while lower-risk questions would be documented, routed, or scheduled with transparent status updates.

Give an example of how you would automate a recurring manual data-quality check.

I would identify a stable validation rule, such as ensuring dashboard totals reconcile to a source table within an approved threshold, and translate it into a scheduled SQL test. The test would log results, alert designated owners on failure, retain evidence for auditability, and be documented with escalation guidance and known exceptions.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

About this role.

CentralReach is a leading provider of autism and IDD care software for Applied Behavior Analysis (ABA), multidisciplinary therapy, and special education. Trusted by more than 200,000 users, we enable therapy providers, educators, and employers to scale the way they deliver ABA and related therapies with innovative technology, market-leading industry expertise, and world-class customer satisfaction.

As a Technical Product Analyst at CentralReach, you will sit within the Data Product teams, supporting Product Managers by providing the analytical and technical depth needed to translate requirements into validated, production-ready data products. You will bridge the gap between product strategy and engineering execution, ensuring that the data logic underlying our analytics offerings is as sound as the features built on top of it.

You will work closely with SQL-based data validation, requirements refinement, and process improvement, while also serving as a front-line resource for internal and external stakeholders with questions or issues related to data and dashboards. This is a hybrid role, part product execution, part data QA/validation, part process improvement, suited to someone who is comfortable owning ambiguity in data logic and wants to grow their product and analytical skill set within a fast-moving healthcare data organization.

Responsibilities:

  • Partner with the ABI and DW Product Managers to refine requirements, define acceptance criteria, and support backlog grooming and release readiness.
  • Own SQL-based data validation and metric reconciliation, verifying source-to-target data logic and data transformation into the elasticubes.
  • Direct and interpret output from AI-agent QA tooling, designing test cases and following up on discrepancies.
  • Investigate reported data discrepancies and production issues, distinguishing upstream pipeline problems from BI-layer or presentation issues, and escalate to Engineering when appropriate.
  • Serve as the front-line owner for internal and external user questions on data and dashboards, triaging and resolving requests or routing them to the right team.
  • Support regression testing across releases, ensuring prior fixes and validated logic remain intact as new features and data sources are introduced.
  • Turn recurring manual checks into reusable, documented validation rules, and identify opportunities to automate QA and data-quality workflows.
  • Conduct market, competitive, and data-driven research on an ad hoc basis to support PM decision-making.
  • Maintain clear documentation of requirements, test cases, validation results, and known issues to build a durable artifact trail for both product teams.
  • Communicate validation findings, risk areas, and open issues clearly to PMs, Engineering, and other stakeholders, including status updates during release cycles.

Desired Skills & Experience

  • 2+ years of experience in a data analyst, BI analyst, QA/data validation, or technical product analyst role, ideally in a healthcare or SaaS data environment.
  • Strong proficiency in writing and reading SQL, with the ability to validate data against source-to-target logic rather than relying solely on BI-layer output.
  • Hands-on experience with BI reporting and visualization tools (e.g., Sisense, Tableau, Power BI, Looker), including building and maintaining dashboards, is required.
  • Familiarity with (or ability to quickly learn) elasticube structures and AI-agent tooling.
  • Experience working within Agile/Scrum development processes, including requirements refinement, backlog support, and release readiness.
  • Comfortable owning ambiguity in data logic without needing everything pre-specified, while knowing when to escalate to a PM or Engineering.
  • Strong written documentation habits, with the ability to produce clear requirements, test cases, and QA artifacts.
  • Detail-oriented with strong analytical and troubleshooting skills, able to reconcile discrepancies across multiple data sources.
  • Excellent communication skills, with the ability to work effectively with both technical (Engineering) and non-technical (stakeholder, customer-facing) audiences.
  • Python experience is preferred but not required.
  • Prior exposure to healthcare data, EMRs, or ABA-specific data (billing, scheduling, authorization, clinical session, or clinical goals domains) is preferred but not required.
  • Process-improvement mindset, with an interest in turning recurring manual work into reusable, automated validation rules.

#LI-Remote

Base Salary Range

$85,000—$105,000 USD

Backed by Roper Technologies, Inc. (Nasdaq: ROP), CentralReach is entering an exciting phase of growth, innovation, and scale.

Recognized as one of the best places to work over 10 times by organizations such as Inc, Built In, and NJBIZ, our culture is centered around impact, inclusion, and flexibility. As a hybrid company with collaborative offices in Ft. Lauderdale, FL; Holmdel, NJ; and Verona, Italy, we foster a workplace where top talent can thrive and make a real difference in the lives of those we serve.

We offer competitive compensation, comprehensive health benefits, generous PTO, 401(k) matching, and paid parental leave to our full-time employees. Our team members also enjoy hybrid work schedules, career development support, wellness programs, and opportunities to give back through CR Cares™, our community engagement initiative.

Be part of a market leader driving the future of care. Explore opportunities at centralreach.com/careers.

Protecting your information is important to us. Please take a moment to review our Notice of Privacy Practices for Job Applicants. Applicant-Privacy-Notice-110725 to understand how we collect, use, store, and protect your personal information during the recruitment process.

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