Data Modeler

About the Company

Creospan is a growing tech collective of makers, shakers, and problem solvers, offering solutions today that will propel businesses into a better tomorrow. “Tomorrow’s ideas, built today!” In addition to being able to work alongside equally brilliant and motivated developers, our consultants appreciate the opportunity to learn and apply new skills and methodologies to different clients and industries.

Job Title:

Location:

Hybrid:

Shift timings:

Notice period:

Gap:

Project Overview:

• Creation and management of business data models in all their forms, including conceptual models, logical data models and physical data models (relational database designs, message models and others).
• Expert level understanding of relational database concepts, dimensional database concepts and database architecture and design, ontology and taxonomy design.
• Background working with key data domains as account, holding and transactions within security servicing or asset management space.
• Expertise in designing data driven solution on Snowflake for complex business needs.
• Knowledge of entire application lifecycle including Design, Development, Deployment, Operation and Maintenance in an Agile and DevOps culture.

Role:

This person strengthens the impact of, and provides recommendations on data-models and architecture that will need to be available and shared consistently across the TA organization through the identification, definition and analysis of how data related assets aid business outcomes. The Data Modeler\Architect is responsible for making data trusted, understood and easy to use. They will be responsible for the entire lifecycle of the data architectural assets, from design and development to deployment, operation and maintenance, with a focus on automation and quality.

Must Have Skills:

• 10+ years of experience in Enterprise-level Data Architecture, Data Modelling, and Database Engineering
• Expertise in OLAP & OLTP design, Data Warehouse solutions, ELT/ETL processes
• Proficiency in data modelling concepts and practices such as normalization, denormalization, and dimensional modelling (Star Schema, Snowflake Schema, Data Vault, Medallion Data Lake)
• Experience with Snowflake-specific features, including clustering, partitioning, and schema design best practices
• Proficiency in Enterprise Modelling tools - Erwin, PowerDesigner, IBM Infosphere etc.
• Strong experience in Microsoft Azure data pipelines (Data Factory, Synapse, SQL DB, Cosmos DB, Databricks)
• Familiarity with Snowflake’s native tools and services including Snowflake Data Sharing, Snowflake Streams & Tasks, and Snowflake Secure Data Sharing
• Strong knowledge of SQL performance tuning, query optimization, and indexing strategies
• Strong verbal and written communication skills for collaborating with both technical teams and business stakeholders
• Working knowledge of BIAN, ACORD, ESG risk data integration

Nice to Haves:

• At least 3+ in security servicing or asset Management/investment experience is highly desired
• Understanding of software development life cycle including planning, development, quality assurance, change management and release management
• Strong problem-solving skills and ability to troubleshoot complex issues
• Excellent communication and collaboration skills to work effectively in a team environment
• Self-motivated and ability to work independently with minimal supervision
• Excellent communication skills: experience in communicating with tech and non-tech teams
• Deep understanding of data and information architecture, especially in asset management space
• Familiarity with MDM, data vault, and data warehouse design and implementation techniques
• Business domain, data/content and process understanding (which are more important than technical skills). Being techno functional is a plus
• Good presentation skills in creating Data Architecture diagrams
• Data modelling and information classification expertise at the project and enterprise level
• Understanding of common information architecture frameworks and information models
• Experience with distributed data and analytics platforms in cloud and hybrid environments. Also an understanding of a variety of data access and analytic approaches (for example, microservices and event-based architectures)
• Knowledge of problem analysis, structured analysis and design, and programming techniques
• Python, R