Senior QA/QC Data Analyst

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

Not verified checked Jun 7, 2026

Salary

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401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$111,944 U.S. median for this role

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Data From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Company

Company stage

Public-company From the posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Senior QA/QC Data Analyst CDM Smith is seeking a Senior Data Quality Assurance and Quality Control Analyst to join our Digital Engineering Solutions team. This individual will be part of the Development group within the Digital Engineering Solutions team, helping design and implement data validation processes that ensure high data integrity and support robust data pipelines. An ideal candidate will be a critical thinker, proactive, and highly interested in applying new technologies and methods for data quality improvement. This individual must showcase exceptional abilities in developing and implementing QA/QC solutions for AEC initiatives that involve complex datasets and advanced analytics. As a member of the Digital Engineering Solutions team, the individual will be engaged in research and development, providing guidance and oversight into data quality standards and practices at CDM Smith, as well as participating in the evaluation and adoption of innovative technologies and methodologies that arise from across the company. The ideal candidate must have extensive experience in data quality management and a demonstrated commitment to continuous improvement and measurable results. The following are the key responsibilities for this position: • Take responsibility for the project and work independently in a collaborative environment. • Evaluate data across various dimensions, including accuracy, completeness, consistency, validity, timeliness, uniqueness, and integrity. • Establish quality criteria for data accuracy, completeness, consistency, validity, and AI model performance. • Test data ingestion, transformation (ETL/ELT), and outputs to ensure source-to-target integrity. • Verify that datasets used for AI/ML are accurate, representative, unbiased, and fit for purpose.

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