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Sequential Technology International

Data Modeler / Architect

Sequential Technology International Posted: 26 Month
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Job Title:                                 Data Modeler / Architect                           

Location:                                Philippines                 

Reports to:                              Manager IT                             


 Hybrid working set-up



The Data Modeler/Architect is responsible for translating the enterprise business needs into conceptual, logical and physical data models. Provides expertise on data modeling tools, techniques and best practices and leads the design and implementation of the data architecture and data modeling solutions supporting enterprise information management, business intelligence, machine learning, data science, and other business interests across relational, dimensional and NoSQL databases. Has solid knowledge of data architectures, data stewardship and data governance.


Responsible for articulating modeling principles, visualize relationships between key business concepts and entities, create conceptual level data dictionaries, possess in-depth knowledge of Data warehousing, a top-notch data modeler designing data models that reduce data redundancy, streamlines data movements, and improves enterprise information management. The candidate must be able to work independently and collaboratively partnering with cross location business and technical teams



Essential Responsibilities:

·        Experience in Data Warehouse, Data Architecture, Design, Analysis, Modeling, Development, Testing, Implementation, Training and Documentation.

·        Hands on experience in creating database schemas, SQL, PLSQL programming and End-to-End ETL validations.

·        Experience with modeling tools like Erwin, Talend for Data Transformation (ETL) and Power BI Reporting

·        Experience in defining & implementing Data Management Strategies: -Data acquisition (Data integration & ETL), data inventory control (data cataloging) & data storage

·        Experience in Data Governance policies, practices: - covering data quality, accuracy, security & correctness

·        Experience in descriptive, diagnostic, predictive or prescriptive Data Analytics

·        Experience in Snowflake schema methods, identifying the dimensions, measures, Hierarchy levels for Fact and Dimension tables.

·        Strong in both Star schema and OLTP Schema

·        Expertise in designing for late arriving data and factless facts

·        Work with business and application/solution teams to implement data strategies, build data flows, and develop conceptual/logical/physical data models

·        Define and govern data modeling and design standards, tools, best practices, and related development for enterprise data models.

·        Define and maintain accurate functional data definitions and taxonomies for entities and attributes.

·        Working knowledge in Analysis Services (SSAS) and Integration Services (SSIS)

·        Exposure to Azure cloud components like Data Factory, Data Lake, SQL Database

·        Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualization.

·        Work proactively and independently to address project requirements and articulate issues/challenges to reduce project delivery risks.

·        Research latest data technologies and develop proof of concept

Additional Skills/Requirements

·        Contact center domain knowledge and business data models

·        Knowledge of mathematical foundations and statistical analysis.

·        Analytical, flexible, team-oriented and have good interpersonal/communication skills

Education and/or Experience:

·        Bachelor's degree in Computer Science, or related technical discipline

·        8+ years of experience in designing and implementing EDW, BI & A solutions

·        Minimum 4 plus years of experience in Entity Relationship Models, Star Schema, Dimensional Modeling, and other Data Modeling Techniques and Methodologies

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