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Data Modeller (Enterprise)
Data Modeller (Enterprise)

Data Modeller (Enterprise) at TalentXO · Bengaluru (Bangalore), Mumbai, Hyderabad, Gurugram · 8 - 14 years · ₹30L - ₹40L / yr · Profitable · Posted 17 Mar 2026

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Data Modeller (Enterprise)

tabbasum shaikh's profile picture
Posted by tabbasum shaikh
8 - 14 yrs
₹30L - ₹40L / yr
Bengaluru (Bangalore), Mumbai, Hyderabad, Gurugram
Skills
Data Modelling
SQL
Snowflake

Role & Responsibilities

drives large-scale data modernization and AI readiness for global enterprises. We are looking for an experienced Data Modeler to design, standardize, and maintain enterprise data models across our modernization initiatives — ensuring consistency, quality, and business alignment across cloud data platforms.

The person will be responsible for translating business requirements and data flows into robust conceptual, logical, and physical data models across multiple domains (Customer, Product, Finance, Supply Chain, etc.). You will work closely with Data Architects, Engineers, and Governance teams to ensure data is structured, traceable, and optimized for analytics and interoperability across platforms like Snowflake, Dremio, and Databricks.

Key Responsibilities-

  • Develop conceptual, logical, and physical data models aligned with enterprise architecture standards.
  • Engage with Business Stakeholders: Collaborate with business teams, business analysts and SMEs to understand business processes, data lifecycles, and key metrics that drive value and outcomes.
  • Value Chain Understanding: Analyze end-to-end customer and product value chains to identify critical data entities, relationships, and dependencies that should be represented in the data model.
  • Conceptual and Logical Modeling: Translate business concepts and data requirements into conceptual and logical data models that capture enterprise semantics and support analytical and operational needs.
  • Physical Data Modeling: Design and implement physical data models optimized for performance and scalability
  • Semantic Layer Design: Create semantic models that enable business access to data via BI tools and data discovery platforms.
  • Data Standards and Governance: Ensure models comply with enterprise data standards, naming conventions, lineage tracking, and governance practices.
  • Implement naming conventions, data standards, and metadata definitions across all models.
  • Collaboration with Data Engineering: Work closely with data engineers to align data pipelines with the logical and physical models, ensuring consistency and accuracy from ingestion to consumption.
  • Manage version control, lineage tracking, and change documentation for models.
  • Participate in data quality and governance initiatives to ensure trusted and consistent data definitions across domains.
  • Create and maintain a business glossary in collaboration with the governance team.

Ideal Candidate

  • Strong Enterprise Data Modeller profile (Modern Data Platforms)
  • Mandatory (Experience 1) – Must have 7+ years of experience in Data Modeling or Enterprise Data Architecture, with strong hands-on expertise in designing conceptual, logical, and physical data models for enterprise data platforms
  • Mandatory (Experience 2) – Must have Strong hands-on experience with enterprise data modeling tools such as Erwin, ER/Studio, PowerDesigner, SQLDBM, or similar enterprise data modeling tools
  • Mandatory (Experience 3) – Must have Deep understanding of dimensional modeling (Kimball / Inmon methodologies), normalization techniques, and schema design for modern data warehouse environments.
  • Mandatory (Experience 4) – Proven experience designing data models for modern data platforms such as Snowflake, Databricks, Redshift, Dremio, or similar cloud data warehouse / lakehouse systems.
  • Mandatory (Experience 5) – Must have strong SQL expertise and schema design skills, with the ability to validate data model implementations and collaborate closely with data engineering teams
  • Mandatory (Education) – Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related technical field.
  • Preferred (Experience 1) – Should have familiarity with data governance, metadata management, lineage, and business glossary tools such as Collibra, Alation, or Microsoft Purview.
  • Preferred (Experience 2) – Exposure to data integration pipelines and ETL frameworks such as Informatica, DBT, Airflow, or similar tools.
  • Preferred (Data Management) – Understanding of master data management (MDM) and reference data management principles.
  • Preferred (Domain) – Experience working with high-tech or manufacturing data domains, including customer, product, or supply chain data models


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About TalentXO

Founded :
2018
Type :
Product
Size :
20-100
Stage :
Profitable

About

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Company social profiles

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Location – Hyderabad (Hybrid)

Work Experience – 5 to 7 years

CTC – upto 20 LPA


Roles & Responsibilities:

· We are looking for a Senior Data Engineering who will be majorly responsible for designing, building and maintaining ETL/ ELT pipelines.

· Integration of data from multiple sources or vendors to provide the holistic insights from data.

· You are expected to build and manage Data warehouse solutions, designing data models, creating ETL processes, implementing data quality mechanisms etc.

· Performs EDA (exploratory data analysis) required to troubleshoot data related issues and assist in the resolution of data issues.

· Should have experience in client interaction.

· Experience in mentoring juniors and providing required guidance.

Required Technical Skills

 

· Extensive hands on experience in Python, Pyspark, SQL, Dataiku.

· Strong experience in Data Warehouse, ETL, Data Modelling, building ETL Pipelines, Snowflake database.

· Working knowledge in Databricks, Redshift, ADF etc.

· Hands-on experience in cloud services like Azure, AWS- S3, Glue, Lambda, CloudWatch, Athena.

· Sound knowledge in end-to-end Data management, Data ops, quality and data governance.

· Familiar with SFDC, Waterfall/ Agile methodology.

· Strong domain knowledge in Pharma domain/ life sciences commercial data operations.

 

Qualifications

 

· Bachelor’s or master’s Engineering/ MCA or equivalent degree.

· 5-7 years of relevant industry experience as Data Engineer.

· Experience working on Pharma syndicated data such as IQVIA, Veeva, Symphony; Claims, CRM, Sales etc.

· High motivation, good work ethic, maturity, self-organized and personal initiative.

· Ability to work collaboratively and providing the support to the team.

· Excellent written and verbal communication skills.

· Strong analytical and problem-solving skills. 

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Service Based Company
Service Based Company
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via by Chandra M
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Dear Candidate,


Greeting from NAM Info Pvt Ltd.


We have a role for Data Engineer position with NAM Info.


This role will be permanent with NAM info and deploy to client

location NEW DELHI~CHENNAI~HYDERABAD~PUNE~KOLKATA.


Work Mode: WORK FROM OFFICE

A decent hike can be provided based on current CTC

Interview Mode: Virtual

Role Descriptions:

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Key Responsibilities*

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Location: ~NEW DELHI~CHENNAI~HYDERABAD~PUNE~KOLKATA

Skills: Digital: Databricks, Azure Data Factory

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Descriptions:

Good information and sound knowledge in Azure Synapse Analytics Azure Data Factory (ADF)Big Data technologies and data processing frameworks Azure Data Warehouse and associated Azure data platform services Data integration| data modelling| and performance optimization


Desire candidate

  • Candidate should have valid PF.


Regards,

NAM Info 

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Noora J
Posted by Noora J
Chennai
7 - 25 yrs
₹8L - ₹40L / yr
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Solution Architect – AZURE Data Engineering


Job Overview


We are looking for an experienced Solution Architect – Data Engineering with strong expertise in designing data solutions and hands-on experience with Azure, Synapse, PySpark, Data Warehousing, and Data Lakes. The ideal candidate should have strong architectural and data engineering knowledge.


Key Responsibilities

  • Design and implement scalable data architecture and solutions.
  • Develop and manage Data Warehouse and Data Lake architectures.
  • Design data platforms using Medallion Architecture.
  • Lead Data Engineering and ETL activities.
  • Work with Azure Synapse Analytics for data processing and analytics.
  • Develop data solutions using PySpark / Apache Spark.
  • Define and implement data validation and data quality processes.
  • Collaborate with business, data, and technology teams to deliver effective data solutions.


Required Skills

  • Strong experience in Solution Architecture / Data Architecture.
  • Strong knowledge of Data Warehouse and Data Lake architecture.
  • Good understanding of Medallion Architecture.
  • Strong experience in Data Engineering and ETL.
  • Hands-on experience with Microsoft Azure and Azure Synapse Analytics.
  • Strong knowledge of PySpark / Apache Spark.
  • Experience with Data Validation and Data Quality.
  • Good communication and stakeholder management skills.

Experience

8+ Years

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I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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