Job Description
Senior Cloud Data Modeler - Job Description Introduction
Join an amazing company where you can work with cutting-edge technologies and platforms. Give your career an Infinite edge, with a stimulating environment and a global work culture. Be a part of an organization where we celebrate integrity, innovation, collaboration, teamwork, and passion. A culture where every employee is a leader delivering ideas that make a difference to this world we live in.
In the Senior Cloud Data Modeler responsibilities include, although not limited to:
- Lead the design and delivery of enterprise-grade cloud data models supporting analytics, machine learning, and reporting use cases on Azure and Databricks platforms.
- Own the definition of conceptual, logical, and physical data models aligned with business domains and data product strategies.
- Architect, optimize, and govern Lakehouse data models using Databricks and Delta Lake.
- Monitor and tune data model performance using Databricks compute optimization practices (Zordering, indexing strategies, file optimization, etc.).
- Develop standards for change control and versioning of data models (e.g., branching strategy, schema evolution).
- Experience with schema evolution strategies in Lakehouse environments.
- Knowledge of Medallion Architecture (Bronze/Silver/Gold) best practices.
- Experience designing highvolume streaming data models using Spark Structured Streaming or Event Hubs/Kafka.
- Familiarity with Timetravel, SCD implementation patterns (Type 1/2/3), and Delta Lake transaction logs.
- Hands-on experience with semantic modeling (DBT metrics layer, Power BI semantic models, or LookML).
- Experience with CI/CD for data models (Azure DevOps, GitHub Actions).
- Act as a subject matter expert for cloud data modeling, advising architects, engineers, and business stakeholders.
- Define, document, and enforce modeling standards including dimensional, domain-driven, and Lakehouse-oriented patterns.
- Guide ingestion and transformation pipelines using Databricks, Spark, and Azure Data Factory.
- Ensure data governance, quality, lineage, security, and regulatory compliance across cloud data platforms.
- Optimize data models for performance, scalability, and cost efficiency at enterprise scale.
- Mentor and coach data engineers and analysts on advanced cloud data modeling practices.
- Contribute to data platform roadmap discussions and architectural decision-making.
In addition to the qualifications listed below, the ideal candidate will demonstrate the following traits:
- Senior-level ownership and accountability for data modeling decisions.
- Strong ability to influence technical direction and architectural standards.
- Deep analytical mindset with attention to data semantics and performance.
- Clear, confident communication with both technical and business stakeholders.
- Proactive approach to continuous improvement and platform maturity.
Minimum Qualifications
- Bachelor's degree in Computer Science, Data Engineering, Information Systems, Industrial Engineering, or related field.
- 7+ years of experience in data engineering and cloud data modeling roles.
- Proven senior-level experience designing analytical data models on Azure and Databricks.
- Expert-level SQL skills for analytical and large-scale datasets.
- Strong hands-on experience with Databricks, Apache Spark, and Delta Lake.
- Deep knowledge of dimensional modeling, star/snowflake schemas, and analytical design patterns.
- Experience integrating data models with Azure Data Factory, Databricks Workflows, or similar orchestration tools.
- Understanding of data governance, security, lineage, and privacy in cloud environments.
- Proficiency in Python, Scala, or SQL for transformation and modeling workflows.
- Strong English verbal and written communication skills, including technical leadership discussions.
Preferred Qualifications
- Experience with advanced Databricks capabilities such as Delta Live Tables and Unity Catalog.
- Familiarity with Azure data ecosystem services (ADLS Gen2, Synapse, Microsoft Purview).
- Experience supporting BI semantic layers and enterprise analytics consumption.
- Exposure to data mesh or domain-oriented data product architectures.
- Experience operating in Agile/Scrum delivery environments.
- Proven ability to optimize cloud data platforms for cost, performance, and scalability.
Qualifications
BE
Range Of Year Experience-Min Year
4
Range Of Year Experience-Max Year
8
