Sr. Data Governance Architect

Bitwise Inc.

Pune District

Hybrid

INR 2,000,000 - 3,000,000

Full time

14 days+

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Benefits offered by this job

Best in the industry salary and benefits

Job summary

Bitwise Inc. is looking for a Sr. Data Governance Architect in Pune with 16-18 years of experience in Data & Analytics and 6-7 years of hands-on Data Governance architecture. The ideal candidate will define and lead the enterprise Data Governance operating model, conduct maturity assessments, and partner with business leaders. This role requires advanced knowledge in Data Governance, Compliance, and Data Quality Management. The position offers the industry's best salary and benefits with a hybrid work model.

Qualifications

16 to 18 years overall experience in Data & Analytics.
6–7 years of hands-on Data Governance architecture and delivery experience.
Relevant certifications in data governance or related disciplines.

Responsibilities

Define and own the enterprise Data Governance operating model.
Conduct Data Governance maturity assessments.
Develop phased Data & Process Governance roadmaps.
Lead governance implementation activities.
Partner with business leaders and IT teams.

Skills

Data Governance

Data Quality Management

Metadata Management

Compliance

Data Security

Education

Bachelor’s or Master’s degree in Computer Science

Job description

Sr. Data Governance Architect Pune Full-time 16-18 Yrs

Job Summary

We are seeking a seasoned Data Governance Architect with proven, hands‑on experience in designing, assessing, implementing, and maturing enterprise‑wide Data & Process Governance programs aligned with the DAMA‑DMBOK framework.

This role uniquely combines strategic architecture ownership with analyst‑level execution, enabling the individual to independently assess current‑state maturity, identify governance gaps, recommend and implement remediation roadmaps, and drive measurable governance outcomes across data, analytics, and AI initiatives.

The candidate should have practical experience implementing governance solutions, engaging business and technology stakeholders, strengthening compliance and controls, and enabling AI readiness, regulatory adherence, and operational efficiency through disciplined governance practices.

Responsibilities

Enterprise Data Governance Strategy & Architecture
Define and own the enterprise Data Governance operating model aligned with DAMA‑DMBOK knowledge areas, including:
o Data Governance
o Data Quality Management
o Metadata & Data Catalog
o Master & Reference Data Management
o Data Security, Privacy & Compliance
Establish governance vision, principles, policies, standards, and guardrails across business and technology domains.
Design scalable governance frameworks that support cloud, hybrid, and modern data platforms (lakehouse, analytics, AI)
Architect governance solutions that enable trusted data, stronger control environments, improved decision‑making, and scalable data management practices.
Develop and publish an Enterprise Data Governance Charter including scope coverage (systems/functions), objectives, guiding principles, and decision rights.
Governance Maturity Assessment & Gap Analysis
Conduct formal Data Governance maturity assessments using DAMA‑aligned maturity models.
Evaluate current‑state capabilities across people, process, technology, and data dimensions.
Quantify maturity scores, risk exposure, and compliance readiness.
Identify gaps, risks, and improvement opportunities, supported by empirical evidence and stakeholder inputs.
Roadmap Definition & Governance Transformation
Develop phased, prioritized Data & Process Governance roadmaps with clear milestones, success metrics, and dependencies.
Translate assessment findings into actionable remediation initiatives across:
o Data quality management processes
o Metadata, catalog, and lineage enablement
o Policy enforcement and data controls
Drive end‑to‑end governance implementation, from design through adoption and operationalization.
Implementation & Execution (Hands‑On Ownership)
Lead or directly execute governance implementation activities, including:
o Data policies and standards authoring – assess existing policies/SOPs, draft and institutionalize enterprise policies across themes such as data quality, metadata, access, retention, privacy, lineage, and issue management.
o Define metadata governance scope: business glossary, data assets, ownership, classifications, lineage references.
o Define CDE criteria, identify and prioritize CDEs.
o Data quality rules definition and monitoring.
o Define DQ governance process for rule approval, issue ownership, remediation workflow, and exception management.
o Data lineage and metadata onboarding.
Work closely with platform teams to implement governance tooling (Catalog, DQ, lineage, access controls).
Ensure governance capabilities are embedded into data pipelines, SDLC, and operational workflows.
Ensure governance frameworks support responsible AI, data ethics, and AI lifecycle governance.
Partner with business leaders, IT, data owners, stewards, risk, compliance, and legal teams.
Define and operationalize RACI models for data ownership, stewardship, and custodianship.
Enable governance forums, councils, and review mechanisms.
Act as a trusted advisor to executives on data risk, compliance posture, and AI readiness.
Define and track governance KPIs and maturity progression metrics.
Demonstrate governance value through improvements in data quality, trust, compliance, and operational efficiency.
Continuously refine governance processes based on adoption, feedback, and measurable outcomes.

Qualifications

Bachelor’s or Master’s degree in Computer Science
16 to 18 years overall experience in Data & Analytics with relevant hands‑on Data Governance architecture and delivery experience for at least 6–7 years.
Demonstrated success implementing enterprise‑wide governance programs, not just advisory design.
Relevant certifications in data governance or related disciplines.

Compensation and Benefits