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Data Analytics Team Leader

e-finance
Smart Village, Giza
Posted 4 years ago
25Applicants for1 open position
  • 0Viewed
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Job Details

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Job Description

  • The data modeler designs, implements, and documents data architecture and data modeling solutions, which include the use of relational, dimensional, and NoSQL databases. These solutions support enterprise information management, business intelligence, machine learning, data science, and other business interests.

The successful candidate will:

  • Be responsible for the development of the conceptual, logical, and physical data models, the implementation of RDBMS, operational data store (ODS), data marts, and data lakes on target platforms (SQL/NoSQL).
  • Oversee and govern the expansion of existing data architecture, The candidate must be able to work independently and collaboratively.
  • Implement business and IT data requirements through new data strategies and designs across all data platforms (relational, dimensional, and NoSQL) and data tools (reporting, visualization, analytics, and machine learning).
  • 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.
  • Identify the architecture, infrastructure, and interfaces to data sources, tools supporting automated data loads, security concerns, analytic models, and data visualization.
  • Hands-on modeling, design, configuration, installation, performance tuning, and sandbox POC.
  • Work proactively and independently to address project requirements and articulate issues/challenges to reduce project delivery risks.
  • Understand and translate business needs into data models supporting long-term solutions.
  • Work with the Application Development team to implement data strategies, build data flows and develop conceptual data models.
  • Create logical and physical data models using best practices to ensure high data quality and reduced redundancy.
  • Optimize and update logical and physical data models to support new and existing projects.
  • Maintain conceptual, logical and physical data models along with corresponding metadata.
  • Develop best practices for standard naming conventions and coding practices to ensure consistency of data models.
  • Recommend opportunities for reuse of data models in new environments.
  • Perform reverse engineering of physical data models from databases and SQL scripts.
  • Evaluate data models and physical databases for variances and discrepancies.
  • Validate business data objects for accuracy and completeness.
  • Analyze data-related system integration challenges and propose appropriate solutions.
  • Develop data models according to company standards.
  • Guide System Analysts, Engineers, Programmers and others on project limitations and capabilities, performance requirements and interfaces.
  • Review modifications to existing software to improve efficiency and performance.
  • Examine new application design and recommend corrections if required.

Job Requirements

Qualifications

  • Bachelors or master’s degree in computer/data science technical or related experience.
  • 5+ years of hands-on relational, dimensional, and/or analytic experience (using RDBMS, dimensional, NoSQL data platform technologies, and ETL and data ingestion protocols).
  • Experience with data warehouse, data lake, and enterprise big data platforms in multi-data-center contexts required.
  • Good knowledge of metadata management, data modeling, and related tools (Erwin or ER Studio or others) required.
  • Experience in team management, communication, and presentation.
  • ITIL Expert is a Plus.

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