Data Architect

4 days ago


Milton Keynes Buckinghamshire, United Kingdom Thrive IT Systems Full time

We have one open position of Data Modeler(Banking Domain) with one of our client based at Milton Keynes, UK. This is a permanent position. Role : Data Modeler(Banking Domain)
Mode : Permanent
Hybrid

As a Data Modeler you will play a pivotal role in designing and optimizing data models on the AWS cloud-based object store data platform. Your work will be instrumental in ensuring efficient and effective data processing, analytics, and reporting capabilities, which are essential to our data-driven initiatives.

Data Modeling: Design, develop, and maintain conceptual, logical and physical data models that meet data processing, analytics, and reporting needs with the specific focus on cloud-based data platforms.
Create and maintain data architecture artifacts, including entity-relationship diagrams, data dictionaries and schemas.
Partner with business analysts, data architects and developers to understand data requirements.
Collaborate with stakeholders, to ensure the data models align with business goals and standards.
Work with cloud data platform architects, developers or data engineers to ensure the developed model is optimized for performance, scalability and usability.
Establish or adhere to enforce data modeling best practices and standards, ensuring consistency and accuracy in data representation.
Ability to present and negotiate with stakeholders on data model design decisions and trade-offs.
Should have technical knowledge on cloud data services like S3 object stores, data lakes, Lakehouse, data warehouses etc.
Should have a sound knowledge on data modeling methodologies like ER, Dimensional modeling, Data vault 2.Bachelor's or master’s degree in computer science, Data Engineering, or a related field.
~8 to 12 years of experience in data modeling.
~ Expertise in data modeling and database design concepts.
~ Strong problem-solving and troubleshooting skills related to data modeling and platform specific challenges.
~ Knowledge of data quality and data governance principles.
~ Familiarity with DevOps practices, version control systems, and data warehousing best practices is a plus.
~ Must Have – SQL
~


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