Data Modeling
5-star Inc
Las Vegas, NV, United States
9 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Working hours
Regular working hours
Job source
Tech stack
Amazon S3
Data Analysis
Big Data
Cloud Computing
Cloud Database
Databases
Data Dictionary
Data Governance
Data Mapping
Data Profiling
Data Vault Modeling
Data Warehousing
+13 more
IBM DB2
Apache Hive
Microsoft SQL Server
Oracle (Applications)
Software Engineering
Toad Data Modeler
Cloud Platform System
Snowflake
Data Lineage
Star Schema
Data Management
Data Lakehouse
Amazon Redshift
Requirements
Data Modeling, Data Analysis, Data Modeling, Leadership, Communication Skills, Data Warehousing, Snowflake Schema, Cloud Computing, Amazon Simple Storage Service (S3), Apiary/Beekeeping, * 7 + years of experience in Data Modeling & Data Analysis and should have excellent communication and leadership skills.
- Financial Domain knowledge is plus.
- Should have strong understanding of cloud Datawarehouse like Snowflake and Data modelling skill using Data Vault 2.0.
- Should have in depth understanding or executed new concepts like Data Lakehouse and should have worked on Big Data sources / tools such as Hive , S3 , Trino , HUE, etc.
- Should have done complex (100+ entities/tables) Data Modeling programs in both on-prem and cloud environments.
- Experience in designing normalized, denormalized, relational, dimensional, star and snowflake schemas for cloud, big data and on prem databases using any one of these data modeling tools (Erwin, ER/Studio, Toad Data Modeler, etc.)
- Extensive Data Modeling experience in same or similar bigdata and cloud databases such as Hive, Redshift, Snowflake and on prem databases such as Oracle, SQL Server and DB2
- Should have experience in working with product managers, project managers, business users, applications development team members, DBA teams and Data Governance team daily to analyze requirements, design, development, and deployment technical solutions.
- Should have implemented Bill Inmon and Ralph Kimball methodologies to design data warehouses
- Should have in depth understanding on Data Warehousing, Data Analysis, Data Profiling, Master Data Management (MDM), Data Quality, Data Lineage, Data Dictionary, Data Mapping, Data Policy, and Data Governance.
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