Data Architect - London, United Kingdom - Jefferson Frank

Jefferson Frank
Jefferson Frank
Verified Company
London, United Kingdom

1 month ago

Tom O´Connor

Posted by:

Tom O´Connor

beBee Recruiter
Description

Data Architect - £100, ,000 + Generous package
London based - Hybrid, 2x a week in office

My client are a leading global analytics and digital solutions company.


They bring together robust data, powerful analytics, cloud, artificial intelligence and machine learning to create agile and scalable solutions for world leading businesses within insurance, healthcare, banking, media and many more.


Roles and Responsibilites:


  • Understand and translate business needs into data models and data architecture supporting longterm solutions.
  • Work with the Application Development team to implement data strategies, build data flows and development of data models.
  • Create and maintain conceptual, logical, and physical data models using best practices to ensure high data quality and reduced redundancy, along with corresponding metadata.
  • Optimise and update logical and physical data models to support new and existing projects.
  • Develop best practices for standard naming conventions and coding practices to ensure consistency of data models.
  • Organized and rigorous with versioning of documentation and models to ensure consistent delivery and understanding between the client and development team.
  • 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 datarelated 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.
  • Lead and support setting the data architecture direction (including data movement approach, architecture / technology strategy, and any other datarelated considerations to ensure business value) ensuring data architecture deliverables are developed, compliance to standards and guidelines, implementing the data architecture, and supporting technical developers at a project or business unit level.
  • Coordinate and consult with the project manager, client business staff, client technical staff and project developers in data architecture best practices and anything else that is datarelated at the project or business unit levels.

Desired Qualifications and Experience:


  • 68 years of Enterprise and Dimensional Data Modelling
  • Experience using major data modelling tools (examples: Erwin, ER/Studio, PowerDesigner, etc.)
  • Experience with major database platforms (e.g. Oracle, SQL Server, Teradata, etc.)
  • Understanding and experience with major Data Architecture philosophies (Dimensional, ODS, Data Vault, etc.)
  • 35 years of management experience required
  • 35 years consulting experience preferred
  • Bachelor's degree or equivalent experience, Master's Degree Preferred
  • Experience in data analysis and profiling
  • Experience with major database and big data platforms (e.g. RDS, Aurora, Redshift, Databricks, MySQL, Oracle, PostgreSQL, Hadoop, Snowflake, etc.)
  • Understanding and experience with major Data Architecture philosophies (Dimensional, ODS, Data Vault, etc.)
  • Understanding of modern data warehouse capabilities and technologies such as realtime, cloud, Big Data.
  • Strong understanding of data integration best practices and concepts
  • Strong data warehousing and OLTP systems from a modelling and integration perspective
  • Strong understanding of data integration best practices and concepts
  • Strong development experience under Unix and/or Windows environments
  • Strong SQL skills required scripting (e.g., PL/SQL) preferred
  • Strong Knowledge of all phases of the system development life cycle
  • Understanding of modern data warehouse capabilities and technologies such as realtime, cloud, Big Data.
  • Understanding of on premises and cloud infrastructure architectures (e.g. Azure, AWS, Google Cloud)
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