Reltio MDM Support

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

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.

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.

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.

About Us

We believe the future of software development is AI-native — where engineers operate at a higher level of abstraction and quality remains non-negotiable. 

Incubyte is a software craft consultancy where the “how” of building software matters as much as the “what”.  

We partner with companies of all sizes, from helping enterprises build, scale, and modernize to early-stage founders bring their ideas to life. 

Our engineers operate in an AI-native development model, using AI as a collaborator across the SDLC to accelerate development while upholding the discipline of software craftsmanship. Guided by Software Craftsmanship and Extreme Programming practices, we build reliable, maintainable, and scalable systems with speed, without compromising quality. If this way of building software resonates with you, we’d like to talk. 

Our Guiding Principles 

These principles define how we work at Incubyte. They are non-negotiable. 

Relentless Pursuit of Quality with Pragmatism 

  We build high-quality systems without losing sight of delivery. 

Extreme Ownership 

  We take responsibility end-to-end for decisions, execution, and outcomes. 

Proactive Collaboration 

  We collaborate closely, challenge each other, and solve problems together. 

Active Pursuit of Mastery 

  We continuously improve our craft and raise our bar. 

Invite, Give, and Act on Feedback 

We seek, give, and act on feedback to get better every day. 

Ensuring Client Success 

We act as trusted partners and focus on real outcomes, not just output. 

Job Description

This is a remote position.

Experience Level

2+ years of experience in SQL, Python, and Snowflake (or equivalent cloud data warehouse), Azure Cloud services.

Role Overview

If you're a Data Craftsperson who takes pride in clean, well-tested data solutions and believes in the principles of Extreme Programming, we'd love to meet you. At Incubyte, we're a DevOps organization where developers own the entire release cycle — you'll get hands-on experience across data engineering, analytics, cloud infrastructure, and direct client communication. This role sits primarily in data engineering (80%) with a meaningful analytics component (20%), supporting our client's data systems end-to-end.

What You'll Do

• Design, build, and maintain data pipelines and infrastructure using SQL and Python
• Work within Snowflake to build and optimize data models supporting business use cases
• Parse and process structured and semi-structured data (JSON, XML) from varied sources
• Diagnose issues across raw, intermediate, and summary tables
• Build SQL queries to support repeatable analytics use cases based on stakeholder requirements
• Investigate and resolve data quality issues, including time-sensitive or urgent ones
• Identify opportunities to consolidate models and maintain a single source of truth (SSOT)

Requirements

What We're Looking For

• 2+ years of experience with SQL and relational databases, with the ability to understand complex data relationships and transformations (required)
• 2+ years of experience with Python for data engineering tasks (required)
• Experience with Snowflake or an equivalent cloud data warehouse (required)
• Experience working with Snowflake Coco or any other AI tools(required) 
• Experience parsing JSON and XML data (a plus)
• A strong eye for data quality and attention to detail
• Knowledge of Git (required)
• Knowledge of Azure cloud services such as Azure Data Factory, Azure Blob Storage, and Azure SQL Database (required)
• Knowledge of data infrastructure/modeling tools like DBT, Fivetran (a plus)
• Experience with BI tools like Power BI(a plus, not core to this role)
• Knowledge of Docker, Linux, Shell/Bash, and virtualization technologies (a plus)
• Knowledge of SSIS packages (a plus)
• Familiarity with CI/CD methodologies

Benefits

Life at Incubyte  

We are a remote-first company with structured flexibility. Teams commit to shared rhythms during core hours, ensuring smooth collaboration while maintaining autonomy. Twice a year, we come together in person for a co-working sprint and once a year for a retreat - with all travel expenses covered. 

Our environment is built for crafters: pairing, refactoring, experimenting with AI, and pushing the boundaries of software excellence. We are all lifelong learners, and our work is our passion. 

Perks

• Dedicated learning & development budget. 
• Sponsorship for conference talks. 
• Comprehensive medical & term insurance.
• Employee-friendly leave policies. 
• Home Office fund 
• Medical Insurance

Job Summary

We are seeking a skilled Data Engineer to design, build, and maintain scalable data pipelines and infrastructure. The ideal candidate should have strong expertise in SQL, Python, Linux, and modern data engineering practices to support data integration, transformation, and analytics.

Key Responsibilities

• Design, develop, and maintain ETL/ELT data pipelines.
• Write efficient and optimized SQL queries for data extraction, transformation, and reporting.
• Develop automation scripts using Python for data processing and workflow optimization.
• Work with Linux environments for deployment, monitoring, and troubleshooting.
• Ensure data quality, integrity, and reliability across data platforms.
• Collaborate with data analysts, software engineers, and business stakeholders to deliver data solutions.
• Monitor, troubleshoot, and optimize data pipelines for performance and scalability.
• Implement best practices for data security, governance, and documentation.

Required Skills

• Strong experience in Data Engineering concepts and ETL/ELT processes.
• Proficiency in SQL, including query optimization and database design.
• Strong programming skills in Python.
• Hands-on experience with Linux commands, shell scripting, and system administration basics.
• Experience with relational databases such as PostgreSQL, MySQL, SQL Server, or Oracle.
• Familiarity with Git/version control.
• Strong analytical and problem-solving skills.

Preferred Skills

• Experience with cloud platforms (AWS, Azure, or GCP).
• Knowledge of Apache Spark, Airflow, Kafka, or similar data engineering tools.
• Experience with data warehousing solutions and big data technologies.
• Understanding of CI/CD pipelines and containerization (Docker/Kubernetes).

Qualifications

• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
• Relevant certifications in cloud or data engineering are an added advantage.

Data Engineer – Microsoft Fabric

Location: Pune, India

Work Mode: Hybrid

Experience: 6+ Years

Employment Type: Full-time contactor

Compensation: As per market standards, commensurate with experience and expertise

Shift Timings: 2:00 PM – 11:00 PM IST

Notice Period: 0 – 15 days

About the Role

Jade Business Services (JBS) is seeking a Data Engineer – Microsoft Fabric to join our Pune team and work on enterprise-scale data transformation and analytics initiatives.

We are looking for a hands-on Data Engineer with strong experience in Microsoft Fabric, SQL, Python/PySpark and modern data engineering practices. The candidate will be responsible for building scalable data pipelines, implementing Lakehouse and Warehouse solutions, developing data models and supporting governed, reliable and AI-ready data platforms.

The ideal candidate should be comfortable working with architects, engineering teams and client stakeholders to translate business requirements into scalable and production-ready data solutions.

Roles and Responsibilities

• Design and develop data solutions using Microsoft Fabric, including OneLake, Lakehouse, Warehouse and Data Factory pipelines.
• Build and maintain scalable ETL/ELT pipelines for batch and incremental data processing.
• Develop data ingestion and transformation pipelines using Fabric Data Factory, SQL, Python and/or PySpark.
• Implement Medallion Architecture using Bronze, Silver and Gold layers.
• Work with Lakehouse and Fabric Warehouse for enterprise data processing and analytics.
• Develop and maintain data models, tables, views and optimized SQL queries.
• Build and support semantic models for Power BI and analytical workloads.
• Implement data quality, validation, monitoring and error-handling mechanisms.
• Work with metadata, lineage and governance requirements using Microsoft Purview.
• Implement data security, access controls and role-based permissions across data platforms.
• Support Data Product and domain-oriented data architecture principles.
• Follow DataOps practices including CI/CD, deployment, monitoring and production support.
• Troubleshoot pipeline failures, performance issues and data quality problems.
• Optimize data pipelines, queries and storage for performance and cost efficiency.
• Work closely with Data Architects and business stakeholders to understand requirements and implement technical solutions.
• Participate in technical design discussions, code reviews and architecture reviews.
• Maintain technical documentation, data flow diagrams and pipeline documentation.
• Support production deployments, incident resolution and SLA-driven data platform operations.
• Identify opportunities for automation and AI-assisted improvements across data engineering processes.

Qualifications and Skills

• 6+ years of experience in Data Engineering, Data Integration or Data Platform development.
• Strong hands-on experience with Microsoft Fabric.
• Experience with:
• Microsoft Fabric Lakehouse
• Fabric Warehouse
• OneLake
• Fabric Data Factory / Pipelines
• Semantic Models
• Strong understanding of Lakehouse and Medallion Architecture.
• Strong SQL development and query optimization skills.
• Hands-on experience with Python and/or PySpark.
• Experience developing enterprise ETL/ELT and data integration pipelines.
• Experience with batch and incremental data processing.
• Understanding of data modelling concepts including dimensional modelling.
• Knowledge of data quality, metadata, lineage and data governance.
• Working knowledge of Microsoft Purview.
• Understanding of Data Mesh and Data Product concepts.
• Experience with CI/CD, version control, monitoring and DataOps practices.
• Understanding of cloud security, access controls and data privacy.
• Good troubleshooting and problem-solving skills.
• Strong communication skills and ability to work with distributed and client-facing teams.

Preferred Skills

• Microsoft Fabric or Azure Data certifications.
• Experience migrating workloads from Azure Synapse, SQL Server, Databricks or other data platforms to Microsoft Fabric.
• Experience implementing Medallion Architecture on Microsoft Fabric.
• Experience with Power BI and semantic modelling.
• Exposure to AI/ML, Generative AI or Agentic AI use cases on enterprise data platforms.
• Experience working with Data Products or domain-oriented data solutions.
• Experience in Energy & Utilities, Healthcare, Financial Services or Insurance.
• Experience working with US or international enterprise clients.

What We Expect

The ideal candidate should be hands-on first and capable of independently building, troubleshooting and optimizing Fabric data solutions. You should be able to explain the technical decisions behind your implementation and work effectively with architects and engineering teams to deliver production-ready solutions.

Data Engineer Short Hiring Post

🚨 Hiring: Data Engineer

🔹 Experience: 5–9 Years

🔹 Location: Bangalore / Hyderabad

🔹 Skills: PySpark, Python, SQL, ETL, CI/CD, Data Modeling

🔹 Process: L1 Virtual → L2 F2F Karat Test

🔹 F2F: Bangalore / Hyderabad Location

🔹 Positions: Immediate requirement

⚠️ Note: Candidates must be available for F2F Karat immediately after L1.

#Hiring #DataEngineer #PySpark #Python #SQL #BangaloreJobs #HyderabadJobs #Mphasis #ImmediateJoiners

Location: Hyderabad / Chennai

Experience: 5+ years

Employment type: Full-time, permanent

Work Hours: General Shift

website: www.amazech.com

Qualifications: 

• B.E./B.Tech/M.E./M.Tech in Computer Science, Information Technology, Data Science, or related disciplines.
• Strong academic background with relevant industry experience in Data Engineering and Data Warehousing.

Key Responsibilities:

·       Design, develop, and maintain scalable data warehouse solutions using Snowflake.

·       Write, optimize, troubleshoot, and enhance Snowflake SQL queries with a focus on performance and scalability.

·       Develop and support ETL processes using Talend to ensure reliable and efficient data movement.

·       Collaborate with business, analytics, and application teams to enable reporting, dashboards, metrics, and data exploration capabilities.

·       Perform data analysis and resolve issues across data ingestion, transformation, and reporting pipelines.

·       Debug and troubleshoot Python-based data processing scripts and automation workflows.

·       Implement best practices for data quality, testing, deployment, and code reviews.

·       Work across UI, API, and Data Warehouse layers to support end-to-end data integration and business requirements.

·       Monitor, optimize, and maintain data warehouse performance and operational stability.

·       Create and maintain technical documentation, data models, and process workflows.

Required Skills and Experience: 

·       Strong hands-on expertise in Snowflake Data Warehouse.

·       Advanced SQL skills with experience handling large-scale datasets.

·       Strong understanding of Data Warehousing concepts, dimensional modelling, and data architecture.

·       Hands-on experience with Analytical SQL functions, query tuning, and performance optimization.

·       Experience developing and maintaining ETL solutions using Talend.

·       Proficiency in Python for scripting, debugging, automation, and data processing.

·       Experience integrating UI, API, and Data Warehouse workflows.

·       Strong problem-solving and analytical skills.

·       Experience with testing, code reviews, and deployment best practices.

·       Excellent communication and stakeholder management skills.

Urgent Hiring – Senior Data Engineer

We are hiring for a Senior Data Engineer for a reputed product-based company in Pune.

Location: Pune – Magarpatta / Baner

Experience: 7–10 Years

Work Mode: 5 Days WFO

Notice Period: Immediate to 30 Days preferred

What We're Looking For

• 7+ years of hands-on experience in Data Engineering
• 5+ years of experience in Python
• 4+ years of experience in Snowflake
• 5+ years of experience in SQL
• 5+ years of experience with ADF / Fivetran / Matillion or equivalent Data Integration tools
• Hands-on experience with AWS / Azure
• Experience with Airflow or equivalent orchestration tools
• Strong experience in ETL/ELT and Data Pipelines
• Experience with APIs, JSON, XML and Webhooks
• Knowledge of CI/CD, Git and automated testing
• Exposure to dbt or similar transformation tools
• Experience in data pipeline monitoring, troubleshooting and performance optimization

Key Responsibilities

• Design, develop and maintain scalable ETL/ELT data pipelines
• Build batch, real-time and on-demand data processing workflows
• Integrate data from cloud and on-premise sources
• Ensure data quality, reliability, performance and SLA adherence
• Work closely with Data Scientists, Analysts, DevOps and Business teams
• Implement data engineering best practices, CI/CD and automated testing
• Troubleshoot pipeline issues and perform root cause analysis
• Optimize data pipelines and SQL queries for performance and cost efficiency

Why Join?

• Opportunity to work with a reputed product-based organization
• Work on modern data engineering and cloud technologies
• Exposure to large-scale data platforms and business-critical data solutions
• Collaborative and technically strong environment

Interested candidates can share their updated CV for immediate consideration.