MDM Business Analyst

Role & Responsibilities

Key Responsibilities

• Manage and improve master data across customer, product, entitlement, account hierarchy, product catalog, subscription, contract, billing, and revenue domains.
• Configure and support MDM platform capabilities, including data models, match and merge rules, survivorship rules, hierarchy management, validation rules, workflows, reference data, and data quality rules.
• Support integration of master data between MDM platforms and operational systems such as Salesforce CRM, Salesforce CPQ, Salesforce Revenue Cloud, billing, ERP, data lake, and reporting platforms.
• Assist with customer golden record creation, account hierarchy management, deduplication, data standardization, and Customer 360 enablement.
• Support product taxonomy and product catalog data needed for CPQ bundles, pricing rules, eligibility rules, commercial BOMs, and quote-to-cash automation.
• Maintain entitlement and subscription data, including customer-to-product mappings, lifecycle status, renewals, amendments, upsells, and install base visibility.
• Perform data profiling, cleansing, reconciliation, validation, issue resolution, and root-cause analysis across multiple systems.
• Document data definitions, business rules, source-to-target mappings, lineage, stewardship processes, and remediation actions.
• Partner with Sales Operations, Revenue Operations, Finance, Product Operations, Customer Success, IT, Data Governance, and Enterprise Architecture teams.

Ideal Candidate

• Strong Master Data Management (MDM) Specialist Profile.
• Mandatory (Experience 1) – Must have 3+ years of experience in Master Data Management (MDM), Data Governance, Data Quality, Data Operations, Revenue Operations, Sales Operations, Product Operations, or Enterprise Data Management roles.
• Mandatory (Experience 2) – Must have hands-on experience working with an enterprise MDM platform such as Informatica MDM, Informatica IDMC, Reltio, or any comparable Master Data Management solution.
• Mandatory (Experience 3) – Must have strong experience managing one or more master data domains including Customer Master, Product Master, Product Catalog, Account Hierarchy, Subscription, Contract, Billing, Revenue, Entitlement, or Reference Data.
• Mandatory (Experience 4) – Must have working knowledge of business processes such as CRM, CPQ, Quote-to-Cash (QTC), Order-to-Cash (OTC), Billing, Entitlement Management, Subscription Management, Contract Management, or Revenue Operations.
• Mandatory (Experience 5) – Must have strong understanding of core MDM concepts including Golden Record Creation, Match & Merge Rules, Survivorship Rules, Reference Data Management, Hierarchy Management, Data Stewardship Workflows, Data Quality Rules, and Cross-System Data Synchronization.
• Mandatory (Experience 6) – Must have hands-on experience in data profiling, cleansing, standardization, deduplication, validation, reconciliation, remediation, and data quality improvement initiatives.
• Mandatory (Hike) - AUXO AI follows a compensation policy of offering up to 25% hike on the candidate's current CTC. Candidates whose expectations exceed this range should be screened out during the initial discussion.
• Mandatory (Note) - Only immediate joiners who are available to join within 15 days are considered.
• Mandatory (Domain) – Must have experience working in SaaS, Subscription-based Businesses, Technology Companies, Enterprise Software Organizations, Cloud Product Companies, or Digital Platforms.
• Preferred (Salesforce Ecosystem) – Experience working with Salesforce CRM, Salesforce CPQ, Salesforce Revenue Cloud, Sales Cloud, Service Cloud, or Customer 360 implementations.
• Preferred (MDM Products) – Experience with Informatica Customer 360, Product 360, Reference 360, Cloud Data Quality, Cloud Data Governance, Reltio Connected Data Platform, or Reltio Data Cloud.
• Preferred (Integration Experience) – Experience integrating MDM platforms with Salesforce, CPQ, Billing Systems, ERP Applications, Data Warehouses, Data Lakes, Lakehouse Platforms, or Enterprise Reporting Solutions.

Job Summary

We are seeking an experienced Informatica MDM Developer to design, develop, and implement Master Data Management (MDM) solutions using Informatica IDMC (SaaS). The role focuses on establishing a Single Source of Truth by integrating multiple data sources, enforcing data quality standards, and managing master data domains such as Customer, Product, Supplier, and Employee.

The engineer will collaborate closely with data stewards, data architects, and business stakeholders to deliver high-quality, governed enterprise data. The role requires willingness to support production MDM SaaS platforms and the data warehouse feeding MDM. When capacity permits, the candidate will also support GCP Data Engineering activities

Key Roles & Responsibilities

• Design and build Master Data Management (MDM) solutions using Informatica IDMC (SaaS).
• Create and manage data models for domains like Customer, Product, Supplier, and Employee.
• Configure Business 360 including UI, entities, and business rules.
• Develop and maintain match, merge, and survivorship rules to create accurate golden records.
• Build data integrations using Cloud Data Integration (CDI) and Cloud Application Integration (CAI).
• Develop and support REST APIs for real-time data exchange.
• Implement data quality, cleansing, and standardization rules using Cloud Data Quality (CDQ).
• Support data stewards in resolving data issues, merges, and exceptions.
• Monitor, troubleshoot, and optimize MDM SaaS platform performance.
• Support production MDM systems and the data warehouse feeding MDM.
• Collaborate with business and technical teams to deliver high-quality governed data.
• Willing to support GCP Data Engineering tasks when required (training provided).

Required Skills & Qualifications:

• Hands-on experience with Informatica IDMC (SaaS) including Business 360, Customer 360, or Product 360.
• Strong expertise in CDI, CAI, and CDQ.
• Solid understanding of relational and dimensional data modeling.
• Advanced SQL skills.
• Experience with REST/SOAP APIs, JSON, and XML.
• Familiarity with cloud data platforms such as Snowflake, Databricks, AWS Redshift, or Azure Synapse.

Experience & Education

• Education: Bachelor’s degree in Computer Science, Information Technology, or a related field.
• Experience:
• 3+ years of experience in Master Data Management (MDM).
• 1–2 years of hands-on experience with Informatica MDM SaaS / IDMC.
• Prior experience with Informatica On-Prem Multidomain MDM is a plus (with SaaS migration exposure).

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Job Types: Full-time, Permanent

We are seeking an experienced Informatica MDM Developer to design, develop, and implement Master Data Management (MDM) solutions using Informatica IDMC (SaaS). The role focuses on establishing a Single Source of Truth by integrating multiple data sources, enforcing data quality standards, and managing master data domains such as Customer, Product, Supplier, and Employee.

The engineer will collaborate closely with data stewards, data architects, and business stakeholders to deliver high-quality, governed enterprise data. The role requires willingness to support production MDM SaaS platforms and the data warehouse feeding MDM. When capacity permits, the candidate will also support GCP Data Engineering activities

Key Roles & Responsibilities

• Design and build Master Data Management (MDM) solutions using Informatica IDMC (SaaS).
• Create and manage data models for domains like Customer, Product, Supplier, and Employee.
• Configure Business 360 including UI, entities, and business rules.
• Develop and maintain match, merge, and survivorship rules to create accurate golden records.
• Build data integrations using Cloud Data Integration (CDI) and Cloud Application Integration (CAI).
• Develop and support REST APIs for real-time data exchange.
• Implement data quality, cleansing, and standardization rules using Cloud Data Quality (CDQ).
• Support data stewards in resolving data issues, merges, and exceptions.
• Monitor, troubleshoot, and optimize MDM SaaS platform performance.
• Support production MDM systems and the data warehouse feeding MDM.
• Collaborate with business and technical teams to deliver high-quality governed data.
• Willing to support GCP Data Engineering tasks when required (training provided).

Required Skills & Qualifications:

• Hands-on experience with Informatica IDMC (SaaS) including Business 360, Customer 360, or Product 360.
• Strong expertise in CDI, CAI, and CDQ.
• Solid understanding of relational and dimensional data modeling.
• Advanced SQL skills.
• Experience with REST/SOAP APIs, JSON, and XML.
• Familiarity with cloud data platforms such as Snowflake, Databricks, AWS Redshift, or Azure Synapse.

Experience & Education

• Education: Bachelor’s degree in Computer Science, Information Technology, or a related field.

- Must To Have Skills: Proficiency in SAP Master Data Governance MDG Tool.

- Strong understanding of application development methodologies.

- Experience with integration of SAP MDG with other SAP modules.

- Ability to troubleshoot and resolve application issues effectively.

- Familiarity with data modeling and data governance principles.

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.

Job Description:

Skill Set

Informatica, IDMC, Informatica MDM

Experience

4-6 Years

Location

Faridabad, Haryana, India

Work Mode- Hybrid

Job Description

Roles & Responsibilities

• Lead project team members through all activities required to successfully deliver Informatica.
• Define technical specifications for workflows and business rules.
• Prepare detailed design documents for data migration.
• Configure, build and unit test Informatica components, including data structures, roles, workflows, and portals.
• Train and mentor colleagues in Informatica implementation activities and best practices.
• Support integration, system, and user acceptance testing.
• Accountable for the Master Data Management, Technical Architecture, providing data modeling solutions and recommendations.
• Profile & Analyze Source Data usage using ETL tool.
• Automation, job scheduling, dependencies, monitoring.
• Configure/Script Business rules and transformation rules in ETL
• Data pipeline using IICS
• Hands on experience in Informatica MFT, Data Exchange (DX),and Data Transform (DT) modules
• Integration experience using various adapters (MLLP, SOAP, REST, SFTP, ODBC) will be essential.
• Strong knowledge and experience with developing complex SQL Queries, stored procedures, and triggers for RDBMS systems.
• Experience in administering, supporting, and performance tuning using Informatica.

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.

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

Years of Exp: 5 to 8 Years (Relevant 5+ Years)

Location: Hyderabad

Notice Period: Immediate to 20 days

Offshore: Data Governance Analyst

Position Summary

Execute day-to-day Data Governance activities for RTB initiatives under the direction of the Onshore Lead. The role will focus on producing accurate, complete, and traceable governance artifacts that support enterprise standards, control requirements, and audit readiness.

Key Responsibilities

Register and maintain data assets, reports, and data products in Collibra and Data Marketplace.

Capture and validate business, technical, and operational metadata.

Document end-to-end data lineage, including sources, targets, transformations, and data movement.

Support business glossary, data classification, ownership, stewardship, and authoritative source documentation.

Assist with data quality rule documentation, issue tracking, and remediation follow-up.

Coordinate with data owners, engineers, architects, and application teams to resolve documentation gaps.

Maintain governance evidence, decisions, status reports, and action items.

Track work through Jira and escalate blockers promptly to the Onshore Lead.

Support multiple RTB workstreams while meeting established quality and delivery expectations.

Required Qualifications

Experience in Data Governance, Data Management, metadata management, lineage, or data quality.

Working knowledge of Collibra or a comparable governance platform.

Understanding of data warehousing, data modeling, ETL/data pipelines, and system-to-system data flows.

SQL proficiency and familiarity with cloud data platforms, preferably Snowflake.

Strong analytical, documentation, communication, and organizational skills.

Ability to work effectively in an onshore-offshore delivery model.

Preferred Qualifications

Experience with Collibra or similar Data Governance Platforms, Jira, Confluence, Cloud Data Solutions, Excel

Financial-services or regulated-industry experience.

Familiarity with Agile delivery and audit or regulatory documentation.

Job Description: Informatica IDMC & Snowflake Developer

Experience: 6+ Years

Required Skills: Informatica IDMC, ETL, Data Warehousing, Snowflake, SQL

Contract Duration: 2 months

Required Technical Skills

• Informatica: Strong hands-on experience with Informatica IDMC, Cloud Data Integration (CDI), Cloud Application Integration (CAI), Mass Ingestion (MI).
• ETL / ELT: Strong understanding of ETL architecture, data integration patterns, incremental loading, and error-handling strategies.
• Data Warehousing: Good understanding of dimensional modelling, data marts, fact and dimension tables, and data warehouse design principles.
• Snowflake: Hands-on experience with Snowflake architecture, SQL, data loading, transformations, performance tuning, and warehouse optimization.
• SQL: Strong proficiency in complex SQL queries, analytical functions, views, stored procedures, and query optimization.
• Database Development: Experience creating and maintaining database objects, validating data, reconciling datasets, and troubleshooting performance issues.

Candidate Profile

• 6+ years of hands-on experience in ETL/ELT development and data integration along with IDMC, Snowflake, Data Warehousing and SQL.
• Strong analytical, problem-solving, and communication skills.
• Ability to work independently, manage priorities, and collaborate effectively with cross-functional teams.
• Proven ability to deliver high-quality, scalable, and maintainable data solutions in an Agile Environment.