Data Governance Analyst

IMMEDIATE JOINERS ONLY

Key Responsibilities:

1                   Data Flow Mapping & Lineage

2                   Design and produce end-to-end data flow maps for critical data items – from market source/core systems, through Data Lake staging, zone 2 and consumption zone 3, to downstream reporting, dashboards and analytics use cases.

3                   Document data lineage and transformations for critical data elements identified in the Master Data Requirements exercise, ensuring traceability that is audit-defensible and supports regulatory, governance and AI-readiness needs.

4                   Map data availability by country/Data Lake against the Product Hierarchy (to profit-centre level), building the consolidated Commercial Data Landscape view of what exists, where it sits (source only, staging, or consumption) and what is not captured at all.

5                   Document cross-system dependencies and cross-border data flows, flagging data residency, privacy and regulatory considerations to the appropriate governance forums.

6                   Data Inventory, Data Model Alignment & Gap Analysis

•                    Own and mature the data asset inventory, catalogue and data dictionary aligned to the consolidated Master Data Requirements Template – resolving “Not Specified”, “TBD” and “validation required” availability statuses through structured validation with Market IT and Data Engineering.

•                    Align business data requirements to the conceptual and logical data model of the target Data Lakehouse, ensuring the dependency between data model design and lineage tracking of critical data items is explicitly documented.

•                    Perform gap and hydration analysis by market and product, quantifying the scale of data that must be brought into the Data Lakes and providing sizing input to the Data Foundation Lead, DAE architects and Data Engineering delivery plans.

•                    Contribute to the Data Consolidation Plan towards a single source of truth, including recommended sequencing based on business priority (Top 200 fields, Horizon 1–3 priorities).

•                    Stakeholder Engagement & Workshops

•                    Work hand-in-hand with the Data Foundation Lead, Data & Analytics Programme Manager, Data Engineers, DAE/infrastructure architects, Local Market IT and Business stakeholders (Regional and Market) as the connective tissue between business data needs and technical implementation.

•                    Plan and facilitate structured interviews and cross-functional validation workshops with business, technology and data stakeholders to corroborate actual operating data flows against documented processes – establishing a fact-based, evidence-backed view rather than relying on documentation alone.

•                    Translate ambiguous business asks into clear data definitions, mapping rules and acceptance criteria that Data Engineering can build against, and play back findings to senior stakeholders in clear, visual, decision-oriented formats.

•                    Manage competing priorities across multiple markets with tact, keeping momentum in an environment of constrained capacity and differing local system landscapes.

•                    Governance, Ownership & Documentation

•                    Produce and maintain the Data Ownership & Accountability Matrix – mapping data owners, stewards and custodians per data asset and highlighting ownership gaps for remediation.

•                    Classify data assets by sensitivity and business function, aligning to Data Protection Policy, PDPA and applicable regulatory expectations (e.g. MAS guidelines) in partnership with Risk & Compliance.

•                    Ensure all data flow maps, lineage records and inventory artefacts are version-controlled, audit-ready and handed over cleanly into BAU data governance processes.

•                    Produce source to Datalake mapping document and data catalogue for missing data elements to complete Datalake hydration

Key Skills

•                    Data flow mapping and lineage documentation – proven ability to draw clear, accurate source-to-consumption data flow maps across complex multi-system, multi-market landscapes.

•                    Data architecture and modelling – strong grasp of conceptual/logical data models, data lake/lakehouse zone architectures (staging, conformed, consumption), data marts and MDM concepts.

•                    Data inventory, catalogue, dictionary and metadata management; familiarity with lineage/catalogue tooling (e.g. Purview, Collibra) and diagramming tools (e.g. Visio, ErWin, Lucidchart).

•                    Hands-on data profiling and validation skills (SQL essential) to verify what actually exists in source systems and lake zones.

•                    Strong stakeholder management – this is critical: able to build trust and drive outcomes across regional leadership, market business teams, Market IT and engineering, and to facilitate effective cross-functional workshops.

•                    Insurance domain knowledge – ideally commercial and specialty lines, with an understanding of policy, claims, reinsurance and underwriting data.

•                    Data quality, governance and privacy concepts, including cross-border data considerations.

•                    Clear written and visual communication – able to make complex data landscapes understandable to executives.

Experience & Qualification Requirements:

•                    8+ years’ experience in data architecture, data business analysis or information architecture roles, with at least:

•                    3+ years documenting data flows, lineage or data landscapes across multi-system / multi-market environments.

•                    Experience in Insurance or Financial Services, ideally within data foundation, data lake or data governance programmes.

•                    Demonstrated delivery of data inventory / data mapping / current-state data landscape assessments involving both business and IT stakeholders.

•                    Relevant certification (e.g. DAMA CDMP, TOGAF, cloud data platform certifications) preferred.

Roles & Responsibilities:-

1. Develop and maintain enterprise data governance strategies, policies, and standards aligned with business goals
2. Manage Microsoft Purview accounts, collections, and RBAC; optimize for large-scale environments (50TB+)
3. Design metadata repositories and maintain business glossaries and data dictionaries
4. Implement ingestion workflows via ADF, REST APIs, PowerShell, Azure Functions
5. Define classification rules and sensitivity labels (PII, PCI, PHI); integrate with MIP, DLP, Insider Risk Management
6. Define KPIs and dashboards to monitor data quality across domains
7. Maintain business glossary with domain owners and stewards; enforce approval workflows
8. Automate governance processes using PowerShell, Azure Functions, Logic Apps
9. Set up dashboards for audit logs, compliance reporting, and metadata coverage
10. Collaborate across business, IT, legal, and compliance teams for role alignment

Ideal Candidate:-

1. Strong Data Governance Lead Profile with deep Microsoft Purview and enterprise governance expertise
2. Mandatory (Experience 1): Must have 7+ years of experience in data governance and data management with at least the recent 3+ years of exposure in Microsoft Purview
3. Mandatory (Experience 2): Must have experience defining, leading, and operationalizing an enterprise data governance framework — strategy, policies, and standards aligned to business goals and regulatory compliance.
4. Mandatory (Tech skill 1): Must be proficient in Microsoft Purview — accounts, collections, RBAC, classification/labelling, DLP, Unified Catalog, Data Map, eDiscovery, Compliance Manager, and lifecycle/records management (ideally at large scale, 50TB+).
5. Mandatory (Tech skill 2): Must be strong in metadata management, lineage mapping (e.g. ADF → Synapse → Power BI), data classification, and security governance (PII/PCI/PHI, sensitivity labels, MIP/DLP)
6. Mandatory (Tech skill 3): Must have experience with data governance tools such as Informatica (Axon), Collibra, Atlan, or IBM IG Catalog.
7. Mandatory (Tech skill 4): Must have experience integrating governance with the Azure data stack (Data Lake, Synapse, SQL DB, Power BI) and Snowflake, and automating via ADF, REST APIs, PowerShell, Azure Functions / Logic Apps.
8. Mandatory (Tech skill 5): Must have experience defining data quality KPIs/dashboards, remediation workflows, and business glossary/stewardship (domain owners, approval workflows, metadata audits)
9. Mandatory (Compliance): Must have strong knowledge of GDPR, CCPA, HIPAA, and SOX compliance requirements.
10. Mandatory (Skill): Must be able to bridge technical governance with business and compliance goals, collaborating across business, IT, legal, and compliance teams, and driving governance training and change management
11. Mandatory (Company): B2B Tech/Consulting/B2B Software

We are looking for a detail-oriented and analytical Data Analyst to join our team. The ideal candidate will be responsible for collecting, analyzing, and interpreting data to identify trends, generate insights, and support business decision-making.

The candidate should be comfortable working with large datasets, creating reports and dashboards, and communicating findings clearly to business stakeholders.

Key Responsibilities

• Collect, clean, organize, and analyze data from multiple sources.
• Identify trends, patterns, anomalies, and business opportunities from data.
• Create dashboards, reports, and visualizations for business teams.
• Track and report key performance indicators (KPIs).
• Perform ad-hoc analysis to support business and management decisions.
• Develop and maintain automated reports where possible.
• Work with stakeholders to understand reporting and analytical requirements.
• Ensure data accuracy, consistency, and quality.
• Present analytical findings in a clear and actionable manner.
• Maintain documentation for reports, dashboards, and data processes.

At Nineleaps, we work on bleeding-edge technology with class-leading engineering practices on products that touch the lives of millions of users. We endeavor on doing things the right way, while also promoting a culture of excellence.

About the Role:

We are looking for a Data Analyst with strong analytical and problem-solving skills to transform complex data into meaningful, actionable business insights. The role involves working with large datasets, conducting deep-dive analysis, driving automation, and supporting data-driven product and business decisions.

Key Responsibilities:

• Analyse historical and large datasets to understand data sources, identify trends and patterns, and uncover meaningful insights.
• Write complex SQL queries and leverage Python to perform data analysis, ad hoc investigations, and solve business problems.
• Create reports and translate analytical findings into clear, concise, and actionable recommendations for stakeholders.
• Identify opportunities to drive automation and process improvements, improving efficiency and reducing manual effort.
• Communicate data-driven insights effectively to both technical and non-technical stakeholders in a clear and impactful manner.
• Maintain accurate documentation, ensure high-quality deliverables, and consistently meet defined timelines.

Requirements:

• 3–6 years of experience in Data Analytics, Business Intelligence, Data Engineering, or a similar analytical role.
• Strong hands-on expertise in Python and advanced SQL, with the ability to work with and analyse large datasets.
• Experience working with Google Sheets, and implementing automation through data pipelines or workflows.
• Strong analytical and problem-solving skills, with the ability to interpret complex data and derive actionable insights.
• Excellent communication skills with the ability to effectively present methods, results, and recommendations to stakeholders.
• Ability to collaborate effectively with remote and geographically distributed teams across different time zones.

Company Link: https://www.nineleaps.com/

Company LinkedIn: https://www.linkedin.com/company/nineleaps/

This role will be permanent with NAM info and deploy to client location Hyderabad & Pune.

Work Mode: WORK FROM OFFICE

Role Descriptions:

• Perform detailed data analysis and support business decision-making
• Gather and document business requirements and translate them into technical specifications
• Work closely with stakeholders to define data needs and reporting requirements
• Create user stories, functional specifications, and support UAT activities
• Ensure alignment between business objectives and data solutions

Required Skills:

• Strong expertise in SQL and data querying
• Proven experience in data analysis, requirement gathering, and stakeholder management
• Ability to translate business requirements into technical solutions and user stories
• Good understanding of data models, reporting, and analytics concepts

Skills: Business Analysis~ORACLE SQL

Locations: ~HYDERABAD~PUNE~

Desire candidate

• Candidate should have valid PF.

Mandatory Skills (Must Have)

• SQL and Database Design (5+ years in enterprise data platforms)

• Python development for automation and platform services (5+ years)

• Linux administration and Shell Scripting in production environments

• Metadata-driven systems and data management platform experience

• Technical leadership of offshore or distributed development teams Wissen Technology

• System analysis, troubleshooting, and production support expertise

• Metadata onboarding, integration, and governance processes

• Stakeholder management and delivery ownership across multiple teams

Key Responsibilities

• Lead developers supporting the Pantheon Metadata platform and related services

• Own end-to-end delivery of metadata onboarding and enhancement initiatives

• Design scalable metadata management solutions and automation capabilities

• Collaborate with architecture, infrastructure, and application teams for enterprise integration

• Participate in solution design reviews and establish development best practices

• Prioritize enhancements with business stakeholders and manage delivery commitments

• Provide production support, troubleshooting, and platform stability improvements Wissen Technology

• Drive modernization initiatives related to metadata lifecycle management

Job Overview:

• Designation: SAP MDM / MDG Consultant
• Experience Required: 4 - 8 Years
• Work Location: Mumbai (Work from Office)
• Employment Type: Full-Time, Permanent
• Compensation: 8 - 16 LPA (based on skills & experience)

Job Description:

• Designing and Implementing MDM Solutions: Creating and configuring SAP MDM repositories, defining data models, and developing data quality rules.
• Data Quality Management: Ensuring data accuracy, consistency, and completeness across various SAP systems.
• Data Governance: Developing and enforcing data governance policies, procedures, and standards.
• Data Migration: Planning and executing data migration strategies for SAP implementations and upgrades.
• Collaboration: Working with business users, IT teams, and other stakeholders to gather requirements, resolve issues, and ensure seamless integration of MDM solutions.
• Training and Support: Providing training and support to end-users on MDM best practices, system functionality, and troubleshooting techniques.
• Documentation: Creating and maintaining comprehensive documentation for MDM processes, procedures, and configurations.
• Monitoring and Auditing: Monitoring data quality, identifying discrepancies, and implementing corrective actions.
• Staying Up-to-Date: Keeping abreast of the latest SAP MDM technologies, tools, and best practices.

Key Skills and Qualifications:

• SAP MDM/MDG Experience: Strong knowledge of SAP MDM/MDG (Master Data Governance) concepts and tools.
• Data Governance and Quality: Understanding of data governance principles, data quality management, and data cleansing techniques.
• SAP Knowledge: Familiarity with SAP modules (e.g., Finance, Sales, Materials Management) and their data structures.
• Data Migration Experience: Experience in data migration projects, including data mapping, cleansing, and validation.
• Problem-Solving and Analytical Skills: Ability to analyze complex data issues, identify root causes, and propose effective solutions.
• Communication and Collaboration Skills: Ability to effectively communicate with technical and non-technical audiences and collaborate with diverse teams.
• Project Management Skills: Ability to manage MDM projects, track progress, and meet deadlines.
• Technical Skills: Knowledge of SQL, ABAP (optional), and other relevant technologies.

Hiring: Data Modeler

Experience: 6+ years

Location: Bangalore/Gurugram/Pune

Required Skills

• Hands-on experience in conceptual, logical, and physical data modeling.
• Strong knowledge of ER modeling, dimensional modeling, star/snowflake schemas, fact/dimension tables, and SCDs.
• Strong SQL skills for data profiling, validation, and quality checks.
• Experience with source-to-target mapping, data dictionaries, metadata, and data lineage.
• Proficiency in Erwin, ER/Studio, or similar modeling tools.
• Exposure to Snowflake, Databricks, Redshift, SQL Server, or other data platforms.
• Understanding of data governance, UAT, reconciliation, and Agile methodologies.
• Strong analytical, documentation, and stakeholder management skills.

Preferred Qualifications

• Experience in enterprise data warehousing or lakehouse modeling.
• Knowledge of data products, data contracts, quality SLAs, and reusable datasets.
• Exposure to dbt, data cataloging, metadata management, and governance tools.
• Ability to work independently in a fast-paced environment.

If interested please share your cv at : snigdhaattheratebeanhr.com

Key Responsibilities

• Implement, configure, and support SAP Master Data Governance (MDG).
• Work on master data domains such as Business Partner, Customer, Supplier/Vendor, Material, and Finance.
• Configure change request types, workflows, validations, derivations, and business rules.
• Work with BRFplus, Floorplan Manager (FPM), and SAP MDG data models.
• Integrate SAP MDG with SAP S/4HANA and SAP ECC systems.
• Perform data replication using SAP DRF (Data Replication Framework).
• Troubleshoot data governance and replication issues.
• Prepare functional specifications and coordinate with ABAP developers.
• Support testing, data migration, deployment, and production incidents.

Required Technical Skills

• SAP MDG configuration and implementation.
• SAP MDG data models and change request management.
• Workflow configuration and approval processes.
• BRFplus, DRF, and SOA/ALE integration concepts.
• Knowledge of SAP S/4HANA and SAP Fiori.
• Understanding of master data quality, governance, and data migration.

We’re looking for a dynamic and driven Data Analyst to join our team of technology enthusiasts. This role is crucial in transforming data into insights that support strategic decision-making and innovation within the insurance technology (InsurTech) space. If you’re passionate about working with data, understanding systems, and delivering value through analytics, we’d love to hear from you.

What We’re Looking For

• Proven experience working as a Data Analyst or in a similar analytical role
• 5+ Years of experience in the field
• Strong command of SQL for querying and manipulating relational databases
• Experience with Power BI for building impactful dashboards and reports
• Familiarity with QlikView and Qlik Sense is a plus
• Ability to communicate findings clearly to technical and non-technical stakeholders
• Knowledge of Python or R for data manipulation is nice to have
• Bachelor’s degree in Computer Science, Statistics, Mathematics, Economics, or a related field
• Understanding of the insurance industry or InsurTech is a strong advantage

What You’ll Be Doing:

• Delivering timely and insightful reports to support strategic decision-making
• Working extensively with Policy Administration System (PAS) data to uncover patterns and trends
• Ensuring data accuracy and consistency across reports and systems
• Collaborating with clients, underwriters, and brokers to translate business needs into data solutions
• Organizing and structuring datasets, contributing to data engineering workflows and pipelines
• Producing analytics to support business development and market strategy