5+ Dimensional modeling Jobs in India

Visionyle is Hiring Senior Data Architect - Data Modeller for Capita

Job Details

Job Title : Senior Data Architect - Data Modeller

Job location : Initial - WFH after it may converted into Hybrid

Payroll firm : Visionyle Solutions ( www.visioyle.com)

Job Type: FTE

Job Description:

Mandatory

• Relevant Experience Required : 7+ years
• Experience in Third normal form, Data Vault, Dimensional (Kimball) data modelling
• Experience / certification in Databricks or Snowflake

Job Description

• Lead the design and implementation of efficient data solutions tailored to meet the specific needs of the clients.
• Design and optimise data architectures following standards and best practices.
• Provide technical leadership to architects, analysts and developers guiding them in the development of high-quality data solutions following best practices.
• Evaluate and recommend appropriate technologies, tools and platforms to support data architecture initiatives.
• Enforce data governance standards, data quality controls and best practices to maintain the accuracy, reliability and security of the data.
• Ensure compliance with regulatory, data privacy, security policies and requirements in Data Management.
• Collaborate with clients to understand requirements and provide guidance.
• Drive initiatives to enhance efficiency and effectiveness.
• Create and maintain comprehensive design documentation to support Project implementation and knowledge transfer.
• Keep up-to-date with industry trends, best practices, and emerging technologies.
• Contribute to proposals and sales efforts
• Mentor and provide guidance to junior team members

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Current CTC :

Expected CTC :

Notice Period / LWD / Joining Time:

Offer in Hand Details (if any) :

Reason for change :

Ok for C2H :

We are looking for an experienced Data Modeler with strong expertise in Conceptual, Logical, and Physical Data Modeling across enterprise-scale data platforms. The ideal candidate will have hands-on experience designing data solutions for Data Warehouses, Data Lakes, Lakehouses, Data Marts, OLTP, and OLAP systems, along with deep exposure to dimensional and enterprise data modeling methodologies.

The role requires close collaboration with business stakeholders, architects, engineering teams, and leadership to design scalable, high-performance, and governance-driven data ecosystems.

Key Responsibilities

Data Modeling & Architecture

• Design and maintain Conceptual, Logical, and Physical Data Models for enterprise applications.
• Develop scalable models for:
• Data Warehouses
• Data Lakes & Lakehouses
• Data Marts
• OLTP & OLAP systems
• Create ER diagrams using tools such as:
• ERwin
• ER/Studio
• Enterprise Architect
• PowerDesigner
• Implement:
• Entity-Relationship Modeling
• Data Vault Modeling
• Dimensional Modeling
• Suggest optimal modeling approaches based on business requirements and target architecture.
• Define and enforce enterprise data modeling standards and best practices.

Data Management & Governance

• Perform:
• Data Extraction
• Data Analysis
• Data Cleansing
• Data Mapping
• Data Profiling
• Create and maintain:
• Source-to-Target Mapping documents
• Data Dictionaries
• Functional Specifications
• Champion:
• Data Lineage
• Metadata Management
• Data Quality Analysis
• Data Governance standards
• Define data retention policies and automated anomaly detection mechanisms.

Collaboration & Delivery

• Collaborate with:
• Business Stakeholders
• Data Owners
• Business Analysts
• Architects
• Data Engineers
• QA Teams
• Guide teams on:
• Data ingestion logic
• Ingestion frequency
• Data consumption patterns
• Testing strategies
• Monitor project progress and provide updates to leadership on milestones and blockers.
• Mentor junior team members and provide technical guidance on analytics design patterns.

Platform & Engineering Support

• Build scalable ETL/ELT pipelines for large-volume data movement.
• Work with DBAs and Engineering teams to optimize physical data models.
• Support model-driven development and repository management.
• Troubleshoot production data model and service issues.
• Research and recommend modern data management technologies and engineering practices.

Required Skills & Experience

Experience

• 4+ years of experience in enterprise data modeling and analytics environments.
• Experience working with hybrid data ecosystems involving:
• Relational Databases
• Distributed Data Platforms
• Cloud-based Data Systems

Technical Skills

• Strong understanding of:
• Data Warehousing concepts & architecture
• OLTP and OLAP systems
• Data Governance & Data Quality
• Industry Data Models (e.g., ACORD)
• Experience designing complex dimensional data models.
• Exposure to ETL tools and data ingestion frameworks.
• Hands-on experience with cloud platforms:
• AWS
• Azure
• GCP

Data Modeling Tools

Experience with one or more of the following:

• ERwin
• PowerDesigner
• ER/Studio
• Enterprise Architect
• MagicDraw
• Business Glossary tools

Leadership & Communication

• Experience leading large teams and enterprise projects.
• Strong stakeholder management and client-facing experience.
• Excellent verbal and written communication skills.
• Ability to explain complex technical concepts to non-technical stakeholders.
• Strong analytical, troubleshooting, and problem-solving skills.
• Familiarity with Agile methodologies.

Preferred Qualifications

• Experience with Data Vault architecture.
• Experience in insurance industry data models such as ACORD.
• Exposure to metadata-driven and automation-first data engineering practices.
• Experience building semantic layers for BI and analytics solutions.

ROLES AND RESPONSIBILITIES:

You will be responsible for architecting, implementing, and optimizing Dremio-based data Lakehouse environments integrated with cloud storage, BI, and data engineering ecosystems. The role requires a strong balance of architecture design, data modeling, query optimization, and governance enablement in large-scale analytical environments.

• Design and implement Dremio lakehouse architecture on cloud (AWS/Azure/Snowflake/Databricks ecosystem).
• Define data ingestion, curation, and semantic modeling strategies to support analytics and AI workloads.
• Optimize Dremio reflections, caching, and query performance for diverse data consumption patterns.
• Collaborate with data engineering teams to integrate data sources via APIs, JDBC, Delta/Parquet, and object storage layers (S3/ADLS).
• Establish best practices for data security, lineage, and access control aligned with enterprise governance policies.
• Support self-service analytics by enabling governed data products and semantic layers.
• Develop reusable design patterns, documentation, and standards for Dremio deployment, monitoring, and scaling.
• Work closely with BI and data science teams to ensure fast, reliable, and well-modeled access to enterprise data.

IDEAL CANDIDATE:

• Bachelor’s or Master’s in Computer Science, Information Systems, or related field.
• 5+ years in data architecture and engineering, with 3+ years in Dremio or modern lakehouse platforms.
• Strong expertise in SQL optimization, data modeling, and performance tuning within Dremio or similar query engines (Presto, Trino, Athena).
• Hands-on experience with cloud storage (S3, ADLS, GCS), Parquet/Delta/Iceberg formats, and distributed query planning.
• Knowledge of data integration tools and pipelines (Airflow, DBT, Kafka, Spark, etc.).
• Familiarity with enterprise data governance, metadata management, and role-based access control (RBAC).
• Excellent problem-solving, documentation, and stakeholder communication skills.

PREFERRED:

• Experience integrating Dremio with BI tools (Tableau, Power BI, Looker) and data catalogs (Collibra, Alation, Purview).
• Exposure to Snowflake, Databricks, or BigQuery environments.
• Experience in high-tech, manufacturing, or enterprise data modernization programs.

Advanced SQL, data modeling skills - designing Dimensional Layer, 3NF, denormalized views & semantic layer, Expertise in GCP services

Role & Responsibilities:

● Design and implement robust semantic layers for data systems on Google Cloud Platform (GCP)

● Develop and maintain complex data models, including dimensional models, 3NF structures, and denormalized views

● Write and optimize advanced SQL queries for data extraction, transformation, and analysis

● Utilize GCP services to create scalable and efficient data architectures

● Collaborate with cross-functional teams to translate business requirements(specified in mapping sheets or Legacy

Datastage jobs) into effective data models

● Implement and maintain data warehouses and data lakes on GCP

● Design and optimize ETL/ELT processes for large-scale data integration

● Ensure data quality, consistency, and integrity across all data models and semantic layers

● Develop and maintain documentation for data models, semantic layers, and data flows

● Participate in code reviews and implement best practices for data modeling and database design

● Optimize database performance and query execution on GCP

● Provide technical guidance and mentorship to junior team members

● Stay updated with the latest trends and advancements in data modeling, GCP services, and big data technologies

● Collaborate with data scientists and analysts to enable efficient data access and analysis

● Implement data governance and security measures within the semantic layer and data model

Responsibilities

• Design and implement Azure BI infrastructure, ensure overall quality of delivered solution 
• Develop analytical & reporting tools, promote and drive adoption of developed BI solutions 
• Actively participate in BI community 
• Establish and enforce technical standards and documentation 
• Participate in daily scrums  
• Record progress daily in assigned Devops items 

Ideal Candidates should have

• 5 + years of experience in a similar senior business intelligence development position 
• To be successful in the role you will require a high level of expertise across all facets of the Microsoft BI stack and prior experience in designing and developing well-performing data warehouse solutions 
• Demonstrated experience using development tools such as Azure SQL database, Azure Data Factory, Azure Data Lake, Azure Synapse, and Azure DevOps. 
• Experience with development methodologies including Agile, DevOps, and CICD patterns 
• Strong oral and written communication skills in English 
• Ability and willingness to learn quickly and continuously 
• Bachelor's Degree in computer science