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Entry Level Data Governance Analyst Jobs in Indiana

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Junior HRIS Analyst

Indianapolis, IN · On-site

Basic understanding of data governance or compliance requirements. Physical Demands & Requirements ... analytics and compliance with applicable legal requirements and Company policies. Need ...

Michelin

Data Engineer

Woodburn, IN · On-site

$102K - $123K/yr

Ensures data quality, performance, security, and compliance with data governance guidelines. * Collaborate with data analysts, business analysts, and data scientists to understand requirements, and ...

Michelin North America

Data Engineer

Woodburn, IN · On-site

$102K - $123K/yr

Ensures data quality, performance, security, and compliance with data governance guidelines. * Collaborate with data analysts, business analysts, and data scientists to understand requirements, and ...

Michelin

Data Engineer

Woodburn, IN · On-site

$102K - $123K/yr

Ensures data quality, performance, security, and compliance with data governance guidelines. * Collaborate with data analysts, business analysts, and data scientists to understand requirements, and ...

BC Forward

Data Engineer IV

Indianapolis, IN · On-site

$69 - $71/hr

Knowledge of data quality frameworks, data governance, and dimensional data modeling. Hands-on AI/ML enablement experience, including feature pipelines or LLM-based analytics workflows. Ability to ...

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Entry Level Data Governance Analyst information

What does a typical day look like for an Entry Level Data Governance Analyst, and how do they collaborate with other departments?

As an Entry Level Data Governance Analyst, your day typically involves monitoring data quality, updating data documentation, and supporting data stewardship activities. You’ll often collaborate with IT teams to ensure data policies are properly implemented and work with business units to address data accuracy issues. Regular meetings with data owners and senior analysts are common, providing opportunities to learn best practices and develop a broader understanding of organizational data flows. This collaborative environment helps you build strong communication skills and positions you for advancement within data management or analytics roles.

How to start a career in data governance?

To start a career as an Entry Level Data Governance Analyst, gain foundational knowledge of data management principles, data quality, and compliance standards. Develop skills in data tools such as Excel, SQL, and data governance platforms, and consider obtaining certifications like CDMP or DAMA-DMBOK to enhance your qualifications.

What are the 5 C's of data governance?

The 5 C's of data governance are typically considered to be Completeness, Consistency, Conformity, Credibility, and Compliance. These principles help ensure data quality, security, and proper management, which are essential for an Entry Level Data Governance Analyst to implement effective data policies and maintain data integrity within an organization.

What is the difference between Entry Level Data Governance Analyst vs Data Analyst?

AspectEntry Level Data Governance AnalystData Analyst
Required CredentialsBachelor's in IT, Business, or related field; certifications like CDMP are a plusBachelor's in Statistics, Mathematics, or related field; certifications like CAP or Microsoft certifications are common
Work EnvironmentCorporate data teams, compliance departments, IT departmentsBusiness units, marketing, finance, or IT teams
Employer & Industry UsageUsed in organizations focusing on data compliance, governance, and qualityUsed across industries for data analysis, reporting, and decision-making

While both roles involve working with data, the Entry Level Data Governance Analyst focuses on data quality, compliance, and policies, whereas the Data Analyst emphasizes data interpretation, reporting, and insights. The former is more compliance-oriented, and the latter is more analysis-driven, though both require strong data skills and foundational certifications.

Will AI replace data governance?

AI cannot fully replace data governance roles like an Entry Level Data Governance Analyst, as these involve overseeing data quality, compliance, and policies that require human judgment. AI tools can assist in automating data management tasks, but human oversight remains essential for ensuring data integrity and regulatory adherence.

What are the key skills and qualifications needed to thrive as an Entry Level Data Governance Analyst, and why are they important?

To thrive as an Entry Level Data Governance Analyst, you need a solid understanding of data management principles, data quality concepts, and a bachelor's degree in information systems or a related field. Familiarity with data governance tools such as Collibra, data cataloging systems, and proficiency in Excel or SQL is often required. Attention to detail, analytical thinking, and effective communication skills help you collaborate across departments and ensure data accuracy. These skills are crucial for supporting organizational data integrity, compliance, and informed business decision-making.

Is a GRC analyst a good entry-level job?

A GRC (Governance, Risk, and Compliance) analyst can be a suitable entry-level role for individuals interested in cybersecurity, compliance, and risk management. It typically requires understanding of regulations, policies, and tools like audit software, making it accessible for those starting in the field. The role offers opportunities to develop skills in governance frameworks and security standards, which are valuable for career growth in information security.

What does an Entry Level Data Governance Analyst do?

An Entry Level Data Governance Analyst helps organizations manage and protect their data by ensuring it is accurate, secure, and used properly. They support the development and enforcement of data policies, monitor data quality, and assist with compliance efforts. Their work often involves collaborating with IT and business teams, documenting data processes, and learning to use data management tools. This role is ideal for those interested in building a career at the intersection of data, technology, and business operations.
What are the most commonly searched types of Data Governance Analyst jobs in Indiana? The most popular types of Data Governance Analyst jobs in Indiana are:
What are popular job titles related to Entry Level Data Governance Analyst jobs in Indiana? For Entry Level Data Governance Analyst jobs in Indiana, the most frequently searched job titles are:
What job categories do people searching Entry Level Data Governance Analyst jobs in Indiana look for? The top searched job categories for Entry Level Data Governance Analyst jobs in Indiana are:
Entry Level Data Governance Analyst jobs near you
Infographic showing various Entry Level Data Governance Analyst job openings in Indiana as of July 2026, with employment types broken down into 1% Locum Tenens, 1% Internship, 83% Full Time, 10% Part Time, 1% Temporary, and 4% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution.
Data Systems/Solutions Engineer

Data Systems/Solutions Engineer

Regenstrief Institute

Indianapolis, IN • Hybrid

$109K - $131K/yr

Full-time

Life, Retirement, PTO

Re-posted 8 days ago

Job description

Position SummaryThe Data Systems / Solutions Engineer serves as a key technical contributor within the Regenstrief Data Services team, functioning as a full-stack DataOps/MLOps engineer supporting research and analytics initiatives. This role is responsible for designing, building, and maintaining scalable, reliable data systems and pipelines that enable high-quality data ingestion, transformation, storage, and analysis.The position emphasizes the development of robust, secure, and reproducible data infrastructure that supports data science, analytics, and AI-driven research. The Engineer applies modern software engineering and data engineering practices to ensure data assets are accessible, well-governed, and aligned with clinical and research requirements.This position is a hybrid position with at least one (1) to two (2) days of onsite activity based on business needs. This position is located in downtown Indianapolis IN.  Essential Duties and ResponsibilitiesData Systems Engineering and Operations:
  • Design, build, and maintain data platforms, pipelines, and services that support research, analytics, and AI/ML workloads.
  • Develop and maintain scalable data architectures using modern data warehouse/lakehouse patterns.
  • Ensure data systems are reliable, performant, and designed for long-term sustainability.
  • Implement and maintain ETL/ELT workflows, data validation, and quality monitoring processes.
DataOps / MLOps Enablement:
  • Implement CI/CD practices for data and ML workflows, including testing, version control, and environment promotion.
  • Support reproducible analytics and ML pipelines, including experiment tracking and model lifecycle considerations.
  • Apply best practices for monitoring, observability, and incident response across data systems.
 Cloud, Security, and Governance
  • Design and maintain cloud-based data solutions using secure and scalable architectural patterns.
  • Apply data governance, access control, and auditing practices consistent with HIPAA-aligned research environments.
  • Ensure appropriate handling of sensitive data through de-identification, access management, and compliance controls.
  • Optimize performance and cost efficiency across compute and storage resources.
Clinical and Research Data Support
  • Work with clinical and research stakeholders to translate domain requirements into technical solutions.
  • Support integration and use of clinical and biomedical data standards (e.g., EHR data, HL7/FHIR, OMOP).
  • Produce well-documented data assets and technical specifications to support reuse and transparency.
Collaboration and Project Support
  • Collaborate with data engineers, researchers, analysts, and project managers to deliver high-quality solutions.
  • Contribute to project planning, estimation, and execution.
  • Serve as a technical resource to team members and stakeholders.
  • Document systems, workflows, and architectural decisions clearly and consistently.
Continuous Learning and Innovation
  • Maintain current knowledge of emerging tools, technologies, and best practices in data engineering and AI.
  • Leverage AI-assisted development tools responsibly to improve productivity and code quality.
  • Participate in continuous improvement efforts across systems, processes, and workflows.
 Knowledge, Skills, and Abilities Technical Knowledge:
  • Proficiency in modern data engineering concepts, including:
    • Data warehouse and lakehouse architectures
    • Dimensional modeling and data transformation patterns
    • SQL and at least one general-purpose programming language (e.g., Python)
  • Experience with CI/CD pipelines and automated testing for data and ML workflows
  • Familiarity with data quality frameworks, lineage tracking, and observability tools
  • Understanding of cloud platforms, identity and access management, and security best practices
  • Knowledge of clinical and biomedical data standards and research workflows preferred
Analytical and Problem-Solving Skills
  • Ability to analyze complex technical problems and implement effective solutions
  • Strong troubleshooting skills across data ingestion, transformation, and delivery layers
  • Ability to balance reliability, performance, and cost considerations
Communication and Collaboration
  • Strong written and verbal communication skills
  • Ability to document technical concepts clearly for both technical and non-technical audiences
  • Demonstrated ability to collaborate effectively in multidisciplinary teams 
 Education and Experience
  • Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field required; Master’s degree preferred.
  • Minimum of three (3) years of professional experience in data engineering, systems engineering, or a related technical role.
  • Demonstrated experience in:
    • Data platform or data pipeline development
    • Cloud-based data system
    • SQL and programmatic data processing
    • DataOps or MLOps practices
 Performance Expectations
  • Works independently within established guidelines and best practices.
  • Produces high-quality work with minimal supervision.
  • Demonstrates sound judgment and attention to detail.
  • Contributes to continuous improvement of tools, processes, and team effectiveness.
 Physical Demands
  • Ability to work standard business hours with flexibility as needed.
  • Ability to sit or stand for extended periods.
  • Ability to operate a computer and standard office equipment.
  •  Ability to lift and move materials up to 20 pounds as needed.
  •  Ability to travel occasionally for meetings or training.
 Work Environment
  •  Hybrid office and research environment.
  •  Fast-paced, deadline-driven setting.
  •  Requires collaboration with internal teams and external partners.
  •  Regular use of computers, communication tools, and office equipment.
  BENEFITS OF WORKING HERE 
  • Work with a variety of diverse professionals in the healthcare industry
  • Free parking
  • Paid holidays, vacation, and sick time
  • Group Life and Voluntary Term Life insurance
  • Long-term and Short-term Disability plans
  • Employee Assistance Program (EAP)
  • Flexible Spending Account (FSA)
  • 403b Retirement Plan with gracious employer contributions
  • Fitness program
  • Pet insurance
  • Qualified employer for loan forgiveness

Please note sponsorship and/or relocation are not available for this position. 

REGENSTRIEF INSTITUTE REQUIRES ALL EMPLOYEES TO RECEIVE THE INFLUENZA VACCINATION ANNUALLY UNLESS APPROVED FOR EXEMPTION. 

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