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Master Data Manager Jobs in Indiana (NOW HIRING)

$130K - $150K/yr

Master Data Management (MDM) integration following data profiling and cleansing. Budgetary Liaison: Serve as the primary point of contact for the Head of EDI to ensure all M&A data work is accurately ...

Technical Product Management Job Category: People Leader All Job Posting Locations: Palm Beach ... SLT and SDI) and SAP Master Data (MDG) * Strong ability to translate complex business requirements ...

The Opportunity As part of the Data Management team, you architect and manage master data management solutions to enhance business processes. As a Senior Manager, you lead large projects and innovate ...

Data Architect

Indianapolis, IN · Remote

$61 - $78.50/hr

Data Governance & Metadata Management - Experience implementing enterprise data catalogs, lineage tracking, data quality rules, master data integration, and security models (RBAC/ABAC, rowlevel and ...

Data Architect

Indianapolis, IN · Remote

$61 - $78.50/hr

Data Governance & Metadata Management - Experience implementing enterprise data catalogs, lineage tracking, data quality rules, master data integration, and security models (RBAC/ABAC, rowlevel and ...

Data Architect

Indianapolis, IN · Remote

$61 - $78.50/hr

Data Governance & Metadata Management - Experience implementing enterprise data catalogs, lineage tracking, data quality rules, master data integration, and security models (RBAC/ABAC, rowlevel and ...

Financial Master Data Management; and, Account Reconciliations. Demonstrates thorough abilities and/or a proven record of success as a team leader, leading technical implementation of EPM (Enterprise ...

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Master Data Manager information

See Indiana salary details

$29.5K

$92.4K

$163.7K

How much do master data manager jobs pay per year?

As of Jul 14, 2026, the average yearly pay for master data manager in Indiana is $92,439.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,800.00 and $119,400.00 per year, depending on experience, location, and employer.

How does a Master Data Manager typically collaborate with other departments to ensure data consistency across the organization?

A Master Data Manager works closely with teams such as IT, finance, operations, and sales to establish and enforce data governance policies. They facilitate regular communication to align data standards and resolve discrepancies, often leading cross-functional meetings to address data quality issues. By collaborating on data integration projects and implementing best practices, Master Data Managers ensure that all departments have access to accurate and consistent information, which is crucial for decision-making and operational efficiency.

Is MDM outdated?

Master Data Management (MDM) remains a vital function for data-driven organizations, ensuring data consistency and accuracy across systems. While new technologies like data lakes and cloud platforms have evolved, MDM practices are still essential for maintaining reliable master data, and professionals in this field need skills in data governance and tools like Informatica or Collibra.

What is the difference between Master Data Manager vs Data Analyst?

AspectMaster Data ManagerData Analyst
Required CredentialsBachelor's degree in Business, IT, or related field; certifications like CDMP or DAMABachelor's degree in Statistics, Mathematics, or related field; certifications like CAP or Microsoft Data Analyst
Work EnvironmentData management teams, IT departments, enterprise systemsBusiness units, analytics teams, reporting departments
Employer & Industry UsageFinance, healthcare, retail, manufacturingMarketing, finance, consulting, technology

The Master Data Manager focuses on maintaining and governing core data assets across an organization, ensuring data accuracy and consistency. In contrast, a Data Analyst interprets data to generate insights and support decision-making. While both roles require data-related skills, the Master Data Manager emphasizes data governance and management, whereas the Data Analyst emphasizes data analysis and reporting.

What are the 4 types of MDM?

Master Data Management (MDM) typically includes four main types: consolidated, registry, coexistence, and centralized. Consolidated MDM creates a single, unified view of data by merging records from multiple sources, while registry MDM maintains links between records without merging. Coexistence MDM allows data to be managed separately but synchronized, and centralized MDM stores all master data in a single repository, often requiring strong data governance and data quality practices.

What are the key skills and qualifications needed to thrive as a Master Data Manager, and why are they important?

To thrive as a Master Data Manager, you need expertise in data governance, data quality management, and strong analytical skills, typically supported by a degree in information systems or a related field. Familiarity with master data management (MDM) platforms like Informatica or SAP MDG, and certifications in data management are highly beneficial. Exceptional communication, attention to detail, and project management abilities help you collaborate across departments and drive data initiatives. These skills ensure accurate, consistent, and reliable data that supports business decision-making and operational efficiency.

What is the role of a master data manager?

A master data manager is responsible for overseeing the organization’s core data assets, ensuring data accuracy, consistency, and integrity across systems. They develop data governance policies, manage data quality initiatives, and collaborate with IT and business teams to maintain reliable master data. Proficiency in data management tools and understanding of data standards are essential for this role.

What is a Master Data Manager?

A Master Data Manager is a professional responsible for overseeing an organization’s critical business data, ensuring its accuracy, consistency, and security across various systems. They develop and implement policies and processes for managing master data, such as customer, product, or supplier information. Their role often involves data governance, quality control, and collaborating with different departments to maintain data integrity. Master Data Managers help organizations make informed decisions by providing reliable data and supporting compliance with regulatory requirements.

What is a master data management job?

A master data management (MDM) job involves overseeing and maintaining an organization’s core data assets to ensure accuracy, consistency, and reliability across systems. Professionals in this role typically work with data governance, data quality tools, and enterprise software to create a unified view of critical information such as customer, product, or supplier data.
What are the most commonly searched types of Master Data jobs in Indiana? The most popular types of Master Data jobs in Indiana are:
What cities in Indiana are hiring for Master Data Manager jobs? Cities in Indiana with the most Master Data Manager job openings:
Infographic showing various Master Data Manager job openings in Indiana as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 15% Part Time, and 2% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $92,439 per year, or $44.4 per hour.
Vice President, Artificial Intelligence & Data

Vice President, Artificial Intelligence & Data

Patrick Industries

Elkhart, IN • On-site

$151K - $189K/yr

Full-time

Re-posted yesterday


Patrick Industries rating

6.4

Company rating: 6.4 out of 10

Based on 44 frontline employees who took The Breakroom Quiz

470th of 527 rated manufacturers


Job description

Patrick Industries, a publicly traded company headquartered in Elkhart, Indiana, invites you to join a team of dedicated Team Members who are passionate about delivering high-quality products and exceptional customer service. As a leading solutions provider serving a diverse range of markets across the United States, our commitment to innovation, quality, and sustainability has positioned us as a high growth, diversified and empowered Team of more than 10,000! Your adventure awaits!
Patrick Industries is building its enterprise AI and data capability from the ground up - and is searching for the executive to lead it. This is a rare "zero-to-one" mandate inside a profitable, acquisitive company with 65+ years of entrepreneurial execution and 85+ operating brands: a staged, multi-year investment behind a use-case portfolio carrying more than $150M of identified value across 70+ initiatives, spanning customer-centric operations, aftermarket commerce, and back-office automation. The Vice President of AI & Data will set the operating model, formulate the AI and data investment strategy, build and scale the delivery team, own the data foundation on which it all depends, and run the engine that turns strategy into production-grade and measurable value.
The Role
Reporting to the Chief Information Officer, the Vice President of AI & Data governs, prioritizes, and delivers the enterprise AI, data, and automation initiatives that drive measurable business value across Patrick Industries. The role is the execution engine behind the enterprise AI strategy - and the steward of the data foundation beneath it - translating prioritized use cases into scalable, production-grade solutions through a DevOps-enabled, agile delivery model, and ensuring a disciplined delivery capability that is fast without being fragile.
Operating at the intersection of business and technology, the VP carries full lifecycle accountability - from intake and prioritization through build, deployment, and scaled adoption - and is expected to stay at the leading edge of a fast-moving field, continuously evaluating new models, agentic frameworks, and tools and translating them into pragmatic, well-governed advantage. The leader drives clear traceability from each use case to defined KPIs and business outcomes, strengthens the data-governance leg of the enterprise Digital Backbone, and aligns delivery to Patrick's IT Strategic Pillars:
  • Innovative Advantage - Scale AI-, data-, and automation-driven capabilities that unlock new business value.
  • Value Optimization - Ensure measurable ROI, efficiency gains, and capital discipline.
  • Agility & Efficiency - Enable rapid, iterative delivery through modern DevOps practices.
  • Resilient Operations - Keep AI and data solutions secure, stable, and well-governed.

Areas of Responsibility
The mandate spans the operating capabilities the VP will stand up to govern, deliver, and sustain AI and data at enterprise scale.
Govern & Direct - set the agenda, control the rules, steer the portfolio
  • AI & Data Strategy & Investment - Own the enterprise AI and data strategy and roadmap, the multi-year investment plan and budget allocation, the operating model and decision rights, and an outcome thesis tied to defined value levers.
  • Data Governance, Policy, Standards & Risk - Own data governance - ownership and stewardship, quality, master data management, access, and lineage - alongside acceptable-use policy, an approved-tool catalog with exception workflow, security/model/vendor risk, and a controls library and risk register.
  • Portfolio & Program Management - Prioritize, sequence, and stage-gate the portfolio; control scope, budget, and resources; manage cadence, milestones, and dependencies; and track value realization and benefits.
  • Training, Change & Adoption - Build AI and data literacy from the executive team to the frontline, role-based training paths, change and communications plans, and a champion network that drives durable adoption.

Deliver & Run - build, run, and sustain the capabilities that produce value
  • Enterprise Data Platform & Architecture - Own the data foundation AI depends on - the lakehouse/fabric bridging 40+ ERPs, the semantic layer, master data management and entity matching, cataloging, and observability - and sequence AI delivery behind data readiness.
  • Product Ownership: LLM Platform & Utilities - Own the roadmap for shared LLMs, agents, APIs, and utilities, with monitoring, observability, evaluation, and quality controls, plus utilization analytics, financials, and vendor management.
  • Product Ownership: AI Solutions - Ensure every production solution has a named owner, a managed backlog and release plan, KPI ownership and user-feedback loops, and disciplined reuse, consolidation, and sunset decisions.
  • Technical Ownership - Set reference architecture, integration patterns, and standards; run SDLC, DevOps, and CI/CD for AI workloads; manage environments, infrastructure-as-code, and reliability (SRE); and own production support and incident response.
  • Knowledge & Content Management - Own curated knowledge bases and sources of truth, content lifecycle and access controls, retrieval infrastructure, and data-quality stewardship with ongoing SME-driven curation.

Building the Team & Delivery Engine
A central part of the mandate is to build the people and platform that make delivery repeatable. The VP will recruit and scale a dedicated team from a small founding core to roughly twenty professionals over three years - solution architecture, AI/ML and software engineering, data engineering and architecture, DevOps/MLOps, product management, and data and solution governance - operating a lean internal model that orchestrates strategic delivery partners and brand adoption rather than depending on them. The team stands up the reusable data platform, pipelines, and engineering playbooks that bend the cost curve so each successive use case is faster and cheaper than the last, while Patrick retains the architecture, intellectual property, and institutional knowledge.
Staying at the frontier of AI and data
  • Maintain an active scan of frontier models, agentic frameworks, and tooling with a disciplined evaluation pipeline that separates durable capability from hype, keeping the approved-tool catalog and reference patterns current without compromising security or governance.
  • Translate emerging capability into pragmatic roadmap and investment decisions, and continuously upskill the team so Patrick's practice compounds rather than ages.

Traceability to the IT Strategy
Every responsibility traces to Patrick's IT Strategic Pillars and the enterprise Digital Backbone (Architecture | Data Governance | Talent) across the Stabilize → Accelerate → Differentiate journey - and, through them, to profitable growth, operational discipline, capital stewardship, and teams built for today and tomorrow.
Strategic Pillar
How this role advances it
Innovative Advantage
Scales AI, data, and automation that expand margin, insight, and competitive differentiation, unlocking new growth across customer, aftermarket, and operations.
Value Optimization
Formulates and governs the AI and data investment for measurable ROI; enforces portfolio discipline, benefits tracking, and total-cost-of-ownership control.
Agility & Efficiency
Operates a product-centric, DevOps-enabled delivery model with a predictable cadence and rapid time-to-value.
Resilient Operations
Keeps AI and data solutions secure, reliable, and well-governed through standards, controls, SRE, and incident response.
Candidate Profile
  • Proven executive leadership in AI, data, automation, advanced analytics, or digital product delivery, with a track record of taking solutions from pilot to enterprise scale.
  • Strategic command of AI and data investment - able to shape a multi-year roadmap and budget, prioritize for ROI, and make disciplined build / buy / partner decisions.
  • Deep experience with modern data platforms and governance (lakehouse/fabric, MDM, cataloging, data quality and lineage) and the modern AI stack (LLMs and agentic systems, RAG, MLOps/LLMOps, cloud) - with the habit of staying at the frontier.
  • Strong experience operating DevOps and agile delivery at enterprise scale, with a disciplined, metrics-driven delivery capability.
  • Experience leading within federated or decentralized business environments and influencing senior business stakeholders.
  • Deep understanding of enterprise governance disciplines - security, data, architecture, and compliance - and executive communication skills suited to C-suite and Board engagement.
  • A builder who thrives in a relatively undefined, zero-to-one environment and is energized by standing up a team, a platform, and an operating model.

Leadership Competencies:
Executing for Results
  • Sets clear and challenging goals while committing the organization to improved performance; tenacious and accountable in driving results.
  • Comfortable with ambiguity; adapts nimbly and leads others through complex situations, taking smart, well-considered risks.
  • Viewed as having high integrity and forethought; acts transparently and consistently, always considering what is best for the organization.

Leadership
  • Leads by example, demonstrating Patrick's principles of effective leadership: Leading for Positive Influence and culture, Leading with Humility, Embracing Responsibility, Communicating with Excellence, Leading with Accurate and Social Awareness, Building Healthy Accountability, and Servant Leadership.
  • A diplomat who promotes healthy debate toward "win-win" outcomes and inspires teams with an approachable style.
  • Thrives in a relatively undefined environment, unafraid to "roll up sleeves" across a wide range of topics, projects, and deliverables.
  • Self-reflective and open to feedback; empowers individuals and teams and drives continuous improvement.

Relationships & Influence
  • Builds strong relationships with stakeholders through emotional intelligence and clear, persuasive communication; inspires trust and followership.
  • Brings notable business understanding and developed relationships across industries and technologies.

At Patrick Industries, BETTER Together is our commitment to being our best while striving to bring out the best in one another as we join forces Individually, as Teams, with our Business Units, with our Customers, our Communities and within our entire Patrick family.
Patrick is an Equal Opportunity Employer.
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