Principal Specialist Data Quality

A Career at HARMAN

As a technology leader that is rapidly on the move HARMAN is filled with people who are focused on making life better. Innovation inclusivity and teamwork are a part of our DNA. When you add that to the challenges we take on and solve together youll discover that at HARMAN you can grow make a difference and be proud of the work you do every day.

Introduction: A Career at HARMAN Automotive

Were a global multi-disciplinary team putting the innovative power of technology to work and transforming tomorrow. At HARMAN Automotive we give you the keys to fast-track your career.

• Engineer audio systems and integrated technology platforms that augment the driving experience
• Combine ingenuity in-depth research and a spirit of collaboration with design and engineering excellence
• Advance in-vehicle infotainment safety efficiency and enjoyment

About the Role

We are seeking an experienced and proactive Data Quality Lead who will be accountable for endtoend enterprise data quality across critical business domains (e.g. Material Business Partner Finance and related master data). This role owns the data quality operating model rule lifecycle monitoring cadence remediation governance and measurable improvementsensuring trusted data is available for business operations analytics and AI use cases.

As part of HARMANs data modernization journey this role will operationalize Microsoft Purview as the enterprise data catalog and governance platform (mandatory) and Microsoft Fabric as the primary platform for data quality execution monitoring and trend analytics. The Data Quality Lead partners with business data stewards and data owners to define quality expectations and drive adoption and collaborates with Digital teams and DQ developers to implement scalable automated and AIenabled data quality capabilities.

What You Will Do

EndtoEnd Data Quality Accountability

• Be accountable for enterprisewide data quality outcomes spanning definition execution monitoring remediation and reporting.
• Establish and govern the complete data quality lifecycle: define implement monitor remediate sustain.
• Drive Critical Data Element (CDE) quality management including prioritization thresholds scorecards and performance reporting.
• Translate data quality issues into business impact and risk and drive resolution through defined governance mechanisms.

Stewardship Enablement & Cadence Governance

• Partner with business data stewards and data owners to define data quality rules acceptance criteria thresholds and exception handling.
• Ensure data quality monitoring and cleansing activities are executed according to agreed cadences (weekly monthly quarterly) with clear ownership.
• Implement operational rhythms including steward reviews backlog triage remediation planning and closure verification.
• Escalate persistent or crossfunctional data quality risks to governance forums (e.g. Data Council) with clear decisions and action requests.

Technology Enablement (Microsoft Purview Mandatory)

• Lead the implementation and adoption of Microsoft Purview as the enterprise platform for:
  • Data cataloging discoverability and stewardship enablement
  • Ownership accountability and governance workflows
  • Lineage visibility and trust signals for certified and verified data
• Ensure data quality transparency is embedded into catalog experiences (e.g. quality status rule coverage definitions and steward contacts).

Data Quality Execution & Monitoring (Microsoft Fabric)

• Partner with data quality developers and platform teams to implement rule execution and monitoring in Microsoft Fabric.
• Define how data quality results are stored trended and surfaced (attribute domain and enterpriselevel rollups; dashboards; scorecards).
• Establish data quality SLAs trend monitoring alerting and action tracking for red/amber conditions.
• Ensure quality controls are embedded early in data pipelines and data products (shiftleft quality).

Automated Remediation & Issue Management

• Design and operationalize automated remediation workflows so data quality issues are:
  • Automatically logged (e.g. ticket or workitem creation)
  • Routed to the appropriate owner steward or system team
  • Prioritized based on business impact and severity
  • Tracked endtoend with full auditability from detection to closure
• Define remediation KPIs (cycle time recurrence backlog burndown verification pass rate) and drive continuous improvement.

AIEnabled Data Quality (Key Expectation)

• Apply AIassisted capabilities to improve and scale data quality including:
  • Intelligent profiling and anomaly detection
  • Automated rule suggestions and pattern discovery
  • Rootcause insights and remediation prioritization
  • Duplicate detection and entity resolution where applicable
• Ensure AIdriven outcomes are transparent governed validated with business stakeholders and aligned with compliance expectations.

Change Management Communication & Culture

• Drive a dataqualityfirst mindset through communications playbooks training and success stories.
• Provide executiveready reporting on progress risks and outcomes with clear calls to action.
• Collaborate with Digital teams analytics teams and business functions to embed data quality standards into operating processes.

What You Need to Be Successful

• 8 years of experience in Data Quality Data Governance or Master Data Management at an enterprise scale.
• Proven experience owning endtoend data quality outcomes including rule lifecycle management monitoring cadence remediation governance and reporting.
• Handson experience with Microsoft Purview for data cataloging governance stewardship enablement and trust/visibility.
• Strong stakeholder management skills working effectively across business teams data stewards and Digital teams within a global matrix organization.
• Ability to define data quality metrics SLAs dashboards and scorecards and to drive measurable sustained improvements.
• Excellent communication facilitation and escalation skills with the ability to influence without formal authority.
• Strong understanding of Critical Data Elements (CDEs) and attributelevel data quality management.
• Exposure to SAP MDG and master data processes; familiarity with data quality tools such as SAP Data Services or SAP Information Steward is a plus.
• Experience implementing automated issue management and workflow integrations (e.g. ticketing or work management systems).
• Demonstrated experience applying AI/ML techniques to improve data quality including profiling anomaly detection rule recommendation and entity matching

Bonus Points If You Have

• Bachelors degree in information systems Data Management Business Engineering or equivalent experience.
• Experience with Microsoft Fabric (or equivalent modern data platforms) for data quality execution monitoring and analytics.
• Experience in automotive manufacturing or complex enterprise environments is desirable.
• Familiarity with data compliance and privacy regulations such as GDPR.

What Makes You Eligible

• Willing to travel up to 5% both domestically and internationally.
• Willing to work in an office or hybrid setup in Bangalore India.

What We Offer

• Flexible work environment allowing for full-time remote work globally for positions that can be performed outside a HARMAN or customer location
• Access to employee discounts on world-class Harman and Samsung products (JBL HARMAN Kardon AKG etc.)
• Extensive training opportunities through our own HARMAN University
• Competitive wellness benefits
• Tuition reimbursement
• Be Brilliant employee recognition and rewards program
• An inclusive and diverse work environment that fosters and encourages professional and personal development

#LI-AD3

HARMAN is proud to be an Equal Opportunity / Affirmative Action employer. All qualified applicants will receive consideration for employment without regard torace religion color national origin gender (including pregnancy childbirth or related medical conditions) sexual orientation gender identity gender expression age status as a protected veteran status as an individual with a disability or other applicable legally protected characteristics.