### **About Axis Max Life**
Axis Max Life Insurance Limited, formerly known as Max Life Insurance Company Ltd., is a joint venture between Max Financial Services Limited (“MFSL”) and Axis Bank Limited.
Axis Max Life Insurance offers comprehensive protection and long\-term savings life insurance solutions through its multi\-channel distribution, including agency and third\-party distribution partners. It has built its operations over two decades through a need\-based sales process, a customer\-centric approach to engagement and service delivery, and a well\-trained human capital.
Axis Max Life has been consistently ranked among the best workplaces by the GPTW Institute, reflecting its commitment to creating a positive and empowering work environment.
- **\#ComeAsYouAre LGBTQIA\+ and PwD candidates of all ages are encouraged to apply***
- *Position** Lead Data Governance **Positions** 1
- *Department** Data Engineering **Department** Data Engineering
- *Reporting to** Head of Data Engineering **Reporting to** Head of Data Engineering
- *Location** Gurgaon **Location** Gurgaon **JOB SUMMARY:**
We are seeking an experienced Data Governance Lead to establish, mature, and continuously evolve the enterprise data governance function at Axis Max Life Insurance. This role owns the long\-term governance vision — building a framework that scales with the organization’s data footprint as new domains, data products, and analytical use cases emerge.
The role operates at the intersection of business and technology — partnering with Data Owners (senior business stakeholders), Data Stewards (business teams), and Data Custodians (Data Engineering and Platform teams) to ensure data assets are governed, discoverable, trusted, and compliant with applicable data protection and insurance regulations.
This is a hands\-on leadership role. The incumbent will define and continuously refine the governance operating model, chair governance councils and working groups, select and implement governance tooling appropriate to the organization’s maturity, and drive sustained adoption across the enterprise.
- *Governance Vision, Framework \& Strategy**
- Define and own the long\-term enterprise data governance vision and multi\-year roadmap aligned to business strategy
- Design the governance framework covering ownership, stewardship, catalog, lineage, data quality, and access control
- Establish and chair the Data Governance Council — setting agenda, cadence, decision rights, and escalation paths
- Own the governance maturity model and scorecard; report progress to executive leadership and the Board on a regular cadence
- *Data Ownership \& Stewardship**
- Identify and onboard Data Owners and Data Stewards across all data domains as they emerge and evolve
- Define RACI for core governance activities — catalog maintenance, DQ remediation, access reviews, KPI changes, regulatory response
- Drive active accountability — ensure owners and stewards are governing in practice, not just in name
- *KPI Registry \& Golden Definitions**
- Build and maintain the enterprise KPI registry covering base and derived KPIs
- Govern KPI definition and formula changes — impact assessment, approval workflow, and version control
- Ensure cross\-domain derived KPIs have clear ownership, input contracts, and reconciliation rules
- *Data Catalog \& Lineage**
- Select, implement, and continuously evolve the enterprise data catalog appropriate to current and future scale
- Drive cataloguing of data products with complete and accurate metadata
- Establish end\-to\-end data lineage — from source ingestion through transformation to consumption
- Define minimum data quality standards per domain covering completeness, uniqueness, validity, timeliness, and consistency
- Establish automated DQ checks integrated into the data pipeline lifecycle
- Build DQ dashboards and proactive alerting — detection ahead of business impact, not after
- *Access Control \& Regulatory Compliance**
- Define and operationalize role\-based and attribute\-based access control aligned to data sensitivity classification
- Drive periodic access reviews and certification — ensure least\-privilege access is sustained over time
- Maintain audit\-ready evidence packs for applicable data protection and insurance regulatory requirements
- Respond to internal audit and regulatory observations; drive closure and continuous improvement
- *Adoption, Enablement \& Change Management**
- Design and deliver governance onboarding and continuous enablement for Data Owners and Stewards
- Create governance playbooks, templates, and self\-service documentation that scale with organizational growth
- Track adoption metrics — catalog usage, DQ coverage, access review completion, stewardship activity
- *Key Technical competencies/skills required**
- *Data Governance \& Frameworks**
- Deep understanding of industry data governance frameworks (DAMA DMBOK, DCAM, or equivalent)
- Experience implementing data ownership, stewardship, and operating models at enterprise scale
- Working knowledge of data protection regulations and insurance sector regulatory requirements
- *Cloud Data Platform (AWS Preferred)**
- Hands\-on experience with cloud\-native data platform services for cataloging, storage, processing, and analytics
- Understanding of identity and access management, resource\-based policies, column\-level security, and tag\-based access control
- Experience leveraging audit logging services for compliance evidence and governance telemetry
- *Data Quality \& Observability**
- Experience with data quality frameworks and the ability to evaluate and adopt tools as the ecosystem evolves
- Ability to define DQ rules, thresholds, and alerting strategies suited to business criticality
- Knowledge of data observability principles and modern data reliability practices
- *Data Catalog \& Lineage**
- Experience implementing or operating enterprise data catalogs and the judgment to select tooling appropriate to scale
- Understanding of metadata management, business glossaries, and automated lineage capture
- Familiarity with lineage visualization across ingestion, transformation, and serving layers
- *Data Modeling \& Architecture**
- Understanding of data lakes, data warehouses, data marts, and modern layered (medallion) architectures
- Familiarity with modern data transformation frameworks and SQL\-based modeling approaches
- Knowledge of schema design, partitioning, data lifecycle management, and cost\-aware architecture
- *Stakeholder Management \& Communication**
- Ability to engage CXO\-level business stakeholders on data governance value and trade\-offs
- Experience running governance councils, working groups, and cross\-functional workshops
- Strong written communication — policies, standards, playbooks, and executive\-ready reporting
- *Desired qualifications and experience:**
- Bachelor’s degree in Computer Science, Engineering, Data Science, or related field (Master’s degree preferred)
- 8\+ years in data engineering, data management, or data governance roles
- 3\+ years in a governance\-focused role with enterprise\-wide scope
- Experience in insurance, financial services, or other regulated industries preferred
- Proven track record of building governance capability from inception and evolving it through successive maturity stages
- *Certifications (Good to Have)**
- CDMP (Certified Data Management Professional) — DAMA International
- AWS Certified Data Analytics or Solutions Architect (or equivalent cloud certifications)
- CIPP/A (Certified Information Privacy Professional — Asia) or equivalent privacy certification
- *State**
Home Office
Gurugram \-90C
AI Data \& Innovation
Data Engineering
04\-Jun\-2026