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Data Validator Jobs in Michigan (NOW HIRING)

Enterprise Data Architect

Livonia, MI · On-site

$104 - $163/hr

Set harmonization, modeling, and data-quality standards, including validation guidelines.* Enforce policies for data engineering, integration, security, and compliance.* Monitor day-to-day data ...

New

Data scientists work closely with data engineers, analysts, and business teams to design analytics ... Develop and validate predictive models using techniques such as regression, random forests ...

Master DataOperations & Change Control: - Own end-to-end master data processes (create/change/inactivate) including request intake, validation, approval workflow, and auditability across master data ...

Data Engineer

Auburn Hills, MI

$108K - $130K/yr

Experience with data quality and validation * Experience with API design * Distributed Computing: Deep expertise in Apache Spark (Core, SQL, and Structured Streaming). * Programming Mastery: Strong ...

Sr Data Architect

Troy, MI · On-site

$64 - $85.50/hr

Validate KPIs across source systems and manage cross-system changes safely. * Systems Integration & Ownership: Own the day-to-day health and data flow of integrations connecting Salesforce, iClassPro ...

New

Enforce data-validation gates for completeness, outliers, and consistency before data reaches enrichment. Incident Management, Release Management & Operational SLAs * Own intake, triage, and ...

Sr Data Architect

Troy, MI · On-site

$120 - $170/hr

Validate KPIs across source systems and manage cross-system changes safely. * Systems Integration & Ownership: Own the day-to-day health and data flow of integrations connecting Salesforce, iClassPro ...

New

Builds and validates predictive models using established algorithms and frameworks. * Generates reports and visualizations to communicate findings to stakeholders. * Assists in troubleshooting data ...

Builds and validates predictive models using established algorithms and frameworks. * Generates reports and visualizations to communicate findings to stakeholders. * Assists in troubleshooting data ...

Perform data profiling and implement data quality rules for assessment and validation * Execute data cleansing and standardization using both built-in and custom data rules * Develop and maintain ...

Builds and validates predictive models using established algorithms and frameworks. * Generates reports and visualizations to communicate findings to stakeholders. * Assists in troubleshooting data ...

Showing results 41-60

Data Validator information

See Michigan salary details

$40.1K

$143.8K

$212.2K

How much do data validator jobs pay per year?

As of Aug 14, 2026, the average yearly pay for data validator in Michigan is $143,829.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,400.00 and $148,200.00 per year, depending on experience, location, and employer.

What skills and qualifications are needed to be a data validator?

To thrive as a Data Validator, you need strong attention to detail, analytical skills, and experience working with large datasets, often supported by a degree in information technology, mathematics, or a related field. Familiarity with data validation tools, database systems (like SQL), Excel, and sometimes industry-standard certifications such as CDMP (Certified Data Management Professional) can be advantageous. Excellent communication, problem-solving abilities, and the capacity to work independently or as part of a team are valuable soft skills. These competencies ensure accuracy, integrity, and reliability in data, which are critical for decision-making and business operations.

What challenges might I face as a data validator, and how can I overcome them?

As a Data Validator, you may encounter challenges like identifying subtle inconsistencies in large datasets, managing tight deadlines for data verification, and adapting to multiple data sources or formats. To overcome these hurdles, it’s important to develop strong troubleshooting skills, stay organized, and leverage automated validation tools whenever possible. Collaborating closely with data engineers and business analysts can also help clarify data requirements and resolve ambiguities. Building a thorough understanding of data processes within your organization will further equip you to handle these challenges effectively and efficiently.

What is a data validator?

A Data Validator is responsible for ensuring the accuracy, consistency, and integrity of data within a system or dataset. They review, clean, and verify data to identify errors, inconsistencies, or missing information. This role is essential in industries that rely on high-quality data for decision-making, such as finance, healthcare, and research. Data Validators use various tools and techniques to cross-check and validate data against predefined standards or business rules. Their work helps maintain data reliability, improves efficiency, and supports better decision-making across an organization.

Infographic showing various Data Validator job openings in Michigan as of August 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% In-person job distribution, with an average salary of $143,829 per year, or $69.1 per hour.

Analytics Engineer/Data Analyst - Michigan

RICEFW Technologies, Inc.

Okemos, MI • On-site

Contractor

Re-posted 11 days ago


Job description

4 days a week onsite in Okemos, MI
Summary:
We are seeking an Analytics Engineer (contract) to support development of scalable analytics pipelines and dashboards using Snowflake, dbt, SQL, and Tableau. The analyst will work across the full data lifecycle-from transforming raw data into analytics-ready datasets to enabling business insights through Tableau. This role requires hands-on experience with modern data stack tools and the ability to convert complex business requirements into structured, reliable data models.
Success in this position requires strong SQL skills, experience with dbt-based data modeling, and the ability to work within Snowflake-based environments. The individual should be comfortable supporting end-to-end data workflows, including pipeline development, validation, and Tableau integration. Success also requires strong analytical thinking, attention to data quality, and the ability to bridge business and technical perspectives. The individual will also provide documentation, support validation of outputs, and contribute to adoption of scalable data solutions across the organization.