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Data Validator Jobs in Michigan (NOW HIRING)

Monitor, validate, and improve data quality across analytics workflows. * Investigate and resolve data pipeline issues, discrepancies, and reporting challenges. * Collaborate with business ...

Monitor, validate, and improve data quality across analytics workflows. * Investigate and resolve data pipeline issues, discrepancies, and reporting challenges. * Collaborate with business ...

Monitor, validate, and improve data quality across analytics workflows. * Investigate and resolve data pipeline issues, discrepancies, and reporting challenges. * Collaborate with business ...

Azure Data Engineer

Grand Rapids, MI · On-site

$110K - $132K/yr

... data validation processes. • Collaborate with data analysts, business stakeholders, and development teams to understand data requirements. • Design data models and support data warehousing ...

Azure Data Engineer

Grand Rapids, MI · On-site

$110K - $132K/yr

... data validation processes. • Collaborate with data analysts, business stakeholders, and development teams to understand data requirements. • Design data models and support data warehousing ...

Azure Data Engineer

Grand Rapids, MI · On-site

$106K - $127K/yr

... data validation processes. • Collaborate with data analysts, business stakeholders, and development teams to understand data requirements. • Design data models and support data warehousing ...

Ensuring the accuracy, consistency, and reliability of data, implementing data validation and quality control processes. * Optimize data pipelines for speed, scalability, and performance, ensuring ...

Ensuring the accuracy, consistency, and reliability of data, implementing data validation and quality control processes. * Optimize data pipelines for speed, scalability, and performance, ensuring ...

AI Data Engineer

Detroit, MI

$113K - $136K/yr

Implement data validation, security, and governance policies to ensure the integrity, accessibility, and compliance of data used in AI models. * Support AI model lifecycle: Collaborate with data ...

Data Scientist

Sterling Heights, MI · On-site

$57 - $58/hr

Ensuring the accuracy, consistency, and reliability of data, implementing data validation and quality control processes. Optimize data pipelines for speed, scalability, and performance, ensuring that ...

Snowflake Data Analyst

Detroit, MI · On-site

$45 - $55/hr

Perform data validation, quality checks, and root cause analysis to ensure data accuracy. * Create and maintain reporting solutions using BI tools such as Power BI or Tableau. * Identify trends ...

Apply consistent quality checks to all audience outputs - validating segment logic, sizing, overlap, consent basis, and channel compatibility - before any activation is triggered. * Identify and ...

Data Platform Engineer

Farmington Hills, MI · On-site

$112K - $135K/yr

Implement data validation, logging, monitoring, and error handling to ensure reliability. * Develop reusable frameworks for data ingestion and transformation. Analytics Enablement * Design and ...

Data Platform Engineer

Farmington Hills, MI · On-site

$112K - $135K/yr

Implement data validation, logging, monitoring, and error handling to ensure reliability. * Develop reusable frameworks for data ingestion and transformation. Analytics Enablement * Design and ...

Data Platform Engineer

Farmington, MI

$112K - $135K/yr

Implement data validation, logging, monitoring, and error handling to ensure reliability. * Develop reusable frameworks for data ingestion and transformation. Analytics Enablement * Design and ...

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Showing results 1-20

Data Validator information

See Michigan salary details

$40.1K

$143.8K

$212.2K

How much do data validator jobs pay per year?

As of Jun 27, 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 is the work of data validation?

A data validator reviews and checks data for accuracy, consistency, and completeness to ensure it meets specified standards. This process often involves using tools like spreadsheets or data validation software and requires attention to detail to prevent errors in data entry or processing.

What qualifications do I need to be a data analyst?

To become a data analyst, you typically need a bachelor's degree in fields like statistics, mathematics, computer science, or related areas. Proficiency in data analysis tools such as Excel, SQL, and statistical software, along with strong analytical and problem-solving skills, is essential. Certifications like the Microsoft Certified Data Analyst Associate or Google Data Analytics Professional Certificate can enhance job prospects.

How much does a validation specialist make in the US?

A validation specialist in the US typically earns between $50,000 and $80,000 annually, depending on experience, industry, and location. The role often requires attention to detail, knowledge of validation processes, and familiarity with regulatory standards such as GMP or ISO.

Is a data analyst a well paid job?

Data analysts typically earn competitive salaries that vary by industry, experience, and location. Entry-level positions may start lower, but with skills in SQL, Excel, and data visualization tools, salaries tend to increase with experience and certifications. Overall, it is considered a well-paying role within the data field.

What are the key skills and qualifications needed to thrive in the Data Validator position, and why are they important?

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 job?

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.

What are popular job titles related to Data Validator jobs in Michigan? For Data Validator jobs in Michigan, the most frequently searched job titles are:
What job categories do people searching Data Validator jobs in Michigan look for? The top searched job categories for Data Validator jobs in Michigan are:
Infographic showing various Data Validator job openings in Michigan as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $143,829 per year, or $69.1 per hour.
MTQIP Clinical Registry Data Engineer

MTQIP Clinical Registry Data Engineer

University of Michigan

Ann Arbor, MI • On-site

$112K - $134K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted yesterday


University Of Michigan rating

8.1

Company rating: 8.1 out of 10

Based on 140 frontline employees who took The Breakroom Quiz

133rd of 541 rated colleges and universities


Job description

How to Apply
A cover letter and resume are required for consideration. Please attach both documents as one file due to system limitations.
In your cover letter, please describe how your experience, career goals, and accomplishments directly relate to this position. Please include examples of your experience developing data pipelines, writing SQL code, automating data workflows, working with clinical or administrative data, supporting ad hoc technical projects, and communicating technical information to both technical and non-technical audiences.
To be considered, you must be legally authorized to work in the United States without the need for employer sponsorship now or at any time in the future.
Mission Statement
MTQIP advances trauma care across Michigan through high-quality clinical data, collaborative quality improvement, and actionable performance feedback to participating trauma centers.
Job Summary
The Michigan Trauma Quality Improvement Program, or MTQIP, is a statewide quality improvement collaborative focused on improving trauma care, outcomes, and data-driven performance across participating Michigan trauma centers.
MTQIP is seeking a Clinical Registry Data Architect to support clinical registry data infrastructure, report exports, data pipelines, automation, and program-wide technical data needs. This position will play a key role in maintaining and improving SQL-based report exports from registry platforms, including Snowflake Reader, and supporting the development of streamlined workflows for data submission, validation, reporting, and analysis. In addition, MTQIP is looking to develop extracts from electronic medical record such as EPIC Clarity, and proficiency in data science concepts such as Large Language Models (LLM).
This role is well suited for a data professional who enjoys working at the intersection of healthcare, technology, quality improvement, and applied data engineering. The ideal candidate will be comfortable working with complex clinical data, translating registry and measure specifications into technical logic, writing and maintaining SQL, supporting data quality checks, and collaborating with clinical, operational, and technical stakeholders.
This position will support MTQIP's clinical registry reporting needs, including report exports from vendor systems, data transformation processes, automation, data validation, ad hoc data and technical projects, and potential future data extraction from electronic health record systems such as Epic. The person in this role will work closely with MTQIP leadership, program managers, analysts, clinicians, participating hospitals, registry vendors, and institutional technical teams.
A typical week may include SQL development, Snowflake query development, data pipeline maintenance, troubleshooting registry export logic, documenting technical specifications, validating data quality, supporting automation, responding to ad hoc technical data requests, participating in stakeholder meetings, and helping translate clinical measure logic into reliable, reproducible data processes.
Responsibilities*
  • Develop, maintain, and troubleshoot SQL-based data exports from clinical registry systems, including Snowflake Reader.
  • Translate registry specifications, data dictionary requirements, and performance measure logic into reproducible SQL queries and export processes.
  • Support the development, maintenance, and documentation of MTQIP data pipelines, including data extraction, transformation, validation, and reporting workflows.
  • Create and maintain automated processes to reduce manual data handling, improve reproducibility, and streamline recurring report production.
  • Provide global MTQIP technical data support across registry reporting, collaborative performance measurement, data validation, vendor data workflows, and internal analytic needs.
  • Support ad hoc technical and data projects, including one-time data extracts, special analyses, data investigations, process improvement efforts, and emerging MTQIP reporting priorities.
  • Work with complex healthcare datasets, including trauma registry data, hospital-submitted data, vendor registry data, and potentially electronic health record data from Epic or related systems.
  • Support clinical registry submission workflows, including mapping, formatting, validation, and preparation of data for reporting and analysis.
  • Partner with clinicians, program staff, analysts, vendors, and institutional technical teams to understand data needs and convert them into scalable technical solutions.
  • Perform data quality checks to identify missing, inconsistent, duplicated, or unexpected values.
  • Document SQL logic, data sources, transformation rules, data validation steps, and recurring operational workflows.
  • Support the creation of standardized datasets for internal analysis, quality improvement reporting, external submission, and collaborative performance measurement.
  • Assist with troubleshooting data discrepancies between registry systems, exported files, analytic datasets, and measure specifications.
  • Participate in planning for data infrastructure improvements, report automation, and long-term data modernization efforts.
  • Communicate technical concepts clearly to both technical and non-technical stakeholders.

Required Qualifications*
  • Bachelor's degree in information systems, computer science, data science, health informatics, statistics, engineering, or a related field, or an equivalent combination of education and experience.
  • At least 3 years of experience in data engineering, database programming, systems analysis, health informatics, analytics programming, or related technical work.
  • Demonstrated experience writing, debugging, maintaining, and optimizing SQL queries, stored procedures, functions, views, or similar database objects.
  • Experience working with relational databases, data warehouses, or cloud-based data platforms.
  • Experience developing or supporting ETL, ELT, data extraction, data transformation, or recurring data export processes.
  • Experience with data cleaning, data validation, and data quality review.
  • Ability to translate business, clinical, operational, or registry requirements into technical specifications and reproducible data logic.
  • Demonstrated ability to document technical workflows, data definitions, code logic, and validation steps.
  • Demonstrated ability to communicate complex technical concepts clearly to technical and non-technical audiences.
  • Strong attention to detail, problem-solving ability, and commitment to producing accurate, reliable, and reproducible data outputs.
  • Ability to work both independently and collaboratively in a mission-driven, quality improvement-focused environment.

Desired Qualifications*
  • Experience with Snowflake, Snowflake Reader, or similar cloud-based data warehouse platforms.
  • Experience with Epic, Clarity, Caboodle, or other electronic health record data sources.
  • Experience working with clinical registry data, trauma registry data, quality improvement data, or hospital administrative data.
  • Experience with healthcare data standards, clinical data dictionaries, registry submission requirements, or measure specifications.
  • Experience with Python, R, Stata, SAS, or another statistical or programming languages used for data transformation, automation, or analysis.
  • Experience with process automation, scheduled jobs, file transfer workflows, APIs, or other recurring data movement processes.
  • Experience supporting ad hoc technical projects, data investigations, and stakeholder-driven analytic requests.
  • Experience using version control tools such as Git.
  • Experience creating reusable, well-documented reporting datasets.
  • Familiarity with healthcare quality improvement, trauma care, collaborative quality initiatives, or clinical performance measurement.
  • Experience working with vendors, external partners, hospital data teams, or multidisciplinary clinical stakeholders.
  • Knowledge of HIPAA, data privacy, data security, and appropriate handling of protected health information.

Why Work at Michigan?
In addition to a career filled with purpose and opportunity, the University of Michigan offers a comprehensive benefits package to help you stay well, protect yourself and your family, and plan for a secure future.
Benefits include generous paid time off, retirement savings options, comprehensive health insurance, dental and vision insurance, life insurance, long-term disability coverage, and flexible spending accounts for healthcare and dependent care expenses.
Modes of Work
This position is eligible for hybrid work, with an expected schedule of four days onsite and one day remote. Hybrid work arrangements are at the discretion of the hiring department and may be reviewed or modified based on operational needs.
Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the course of employment. Learn more about the work modes .
Additional Information
This position will support MTQIP's data infrastructure, registry export workflows, data automation efforts, ad hoc technical data projects, and global MTQIP technical data support. The selected candidate will work with sensitive clinical data and must follow all applicable University of Michigan, Michigan Medicine, MTQIP, and regulatory requirements related to data privacy, data security, and protected health information.
This position may require collaboration with registry vendors, participating hospitals, Michigan Medicine technical teams, and clinical or operational stakeholders.
Background Screening
Michigan Medicine conducts background screening and pre-employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third party administrator to conduct background screenings. Background screenings are performed in compliance with the Fair Credit Report Act. Pre-employment drug testing applies to all selected candidates, including new or additional faculty and staff appointments, as well as transfers from other U-M campuses.
Application Deadline
Job openings are posted for a minimum of seven calendar days. The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled any time after the minimum posting period has ended.
U-M EEO Statement
The University of Michigan is an Equal Opportunity Employer. We are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants, including protected veterans and individuals with disabilities.
Job Detail
Job Opening ID
278120
Working Title
MTQIP Clinical Registry Data Engineer
Job Title
Data Architect Senior
Work Location
Ann Arbor Campus
Ann Arbor, MI
Modes of Work
Hybrid
Full/Part Time
Full-Time
Regular/Temporary
Regular
FLSA Status
Exempt
Organizational Group
Medical School
Department
MM GSA - Administrtn (GSA/ADM)
Posting Begin/End Date
5/27/2026 - 7/03/2026
Career Interest
Information Technology

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About University of Michigan

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The University of Michigan (U-M), based in Ann Arbor, MI, US, is one of America's most esteemed institutions in higher education. Established in 1817, it presides in the industry of education and research, providing a range of services including undergraduate, graduate, and professional education programs. Complementing this is an extensive research activity that has significantly contributed to various fields, from healthcare to engineering, humanities to sports. Upholding its mission "to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values", U-M consistently ranks among the top universities globally, a testament to its tradition of excellence in learning and research, and a deep commitment to innovation and discovery.

Industry

Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

Ann Arbor, MI, US

Year founded

1817

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