Job Seekers, Please send resumes to resumes@hireitpeople.com

Required skills:

Advanced knowledge of data architecture, design and business processes ODS and Data Warehouse environments. Ability to work collaboratively in teams and develop meaningful relationships to achieve common goals. Strong SQL and analytical skills to pull data from Snowflake/Oracle/SQL Server and perform usage analysis and/or data profiling. Understanding of data modelling principles. Experience in developing both logical and physical data models. Maintain the glossary / data dictionary. Be involved in project initiatives to drive alignment to our data principles and standards. Build and maintain strong relationships with our key architects and stakeholders. Understand and document how data is, or will be used, and its implications on people, processes, products and technology Implement appropriate data modelling governance framework Coordinate activities with the Enterprise Data Management team, working together with Enterprise Data Architects.

Required Experience:

12+ years of strong experience working in Data Warehouse environment with heavy emphasis on data modeling/data architecture involving data analysis, design, coupled with strong knowledge of end-to-end data warehouse development life cycle (data integration, conceptual, logical and physical modeling). Hands-on experience with modeling tools, such as: ERWIN or another industry standard tool and knowledge of various features of modeling tool. Strong experience in platforms like Snowflake and/or Oracle.

Other relevant skills include:

Pharma industry experience is a Plus. Ability to manage multiple projects in parallel. Proven track record in consulting, architecture, solutioning and implementation. Understanding of emerging technologies, and their associated impact on enterprise environments.

Detailed Job Description:

Conducts data requirements assessment and design sessions with customers Works with analysts to establish clearly defined business requirements. Work with data suppliers to establish input and interface specifications. Perform data analysis for source system data. Creates conceptual logical and physical models for banking data lake implementations. Design and manages data models in data modeling product Data Modeling, Data Warehousing Dimensional Modeling, Data Modeling for Big data and Metadata Management Data Lake and Big Data modeling experience. Design time variant models that support both point in time historical and current state analysis. Develop the approach for the implementation of Data Management lifecycle components examples include conformance with reference architecture metadata strategy data lake strategy data classification programs data quality.

Education Requirement:   

Bachelor’s Degree in Computer Science, Computer Engineering or a closely related field.