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For Companies At a Glance
- Tasks: Review and optimize data models to support analytical use cases.
- Company: Join a forward-thinking company focused on data strategy and innovation.
- Benefits: Enjoy flexible work options and opportunities for professional growth.
- Why this job: Be part of a dynamic team shaping the future of data management.
- Qualifications: Experience in data modeling, AWS, and strong stakeholder management skills required.
- Other info: Ideal for those passionate about data governance and cloud technologies.
The predicted salary is between 43200 - 72000 £ per year.
Key Responsibilities-
- Review existing domain data mart models/architecture to ensure that they meet the needs of our data strategy and are optimized to support our key analytical use cases.
- Design and develop remediated designs/models and work with engineering and analytical stakeholders across the different domains to create backlogs for model standardization and improvements.
- Ensure storage and consumption approaches/designs deliver maximum efficiency, with a focus on balancing storage and compute costs optimally.
- Produce and maintain modelling and design guardrails, standards and processes and integrate these with wider data management and engineering governance, for example:
- Data query performance
- Data table structures
- Partitioning of data across S3 and other object stores
- Data Lifecycle Management – especially in AWS S3 and other cloud object file systems where storage costs are key
- Where and how business logic is developed, tested, approved and embedded
- Who can create permanent or semi-permanent data, where it can be created and how it is managed
- How data is presented and accessed
- Review data modelling and technical approaches to ensure that they are consistent and of high quality.
Skills
- An experienced, driven expert in a broad set of data capabilities such as:
- Data design patterns and optimization across disparate mediums within a Cloud-based environment (preferably AWS) such as large object file systems (AWS S3), RDBMS and columnar databases
- A strategic thinker who can define modelling patterns for various layers of a data environment balancing storage vs. compute costs, optimized for as broad a set of use cases as possible
- Extensive data modelling experience, from conceptual to physical
- Expertise in different modelling methodologies such as 3NF, Dimensional, Data Vault
- Expertise in building cloud data warehouses using Kimball, preferably using AWS Redshift
- Knowledge/experience of building queries and MI outcomes utilizing data visualization technologies (e.g., Tableau)
• Qualifications in RDMBS design and/or administration and in AWS architecture (at least one of these)
• Awareness of data governance and data ethics in the production of automated modelling
• Proven track record of delivery of modelling designs/approaches in large scale data environments
• Evidence of broad stakeholder management from senior business level down to analyst
• Experience in or extensive exposure to MI/BI use cases, data exploration and analysis. Experience within predictive modelling/Data Science would be an advantage
• Experience in defining and delivering data monitoring across a large platform as well as establishing governance forums, processes and guardrails to ensure compliance with standards.
Data Modeler employer: E-Solutions
Contact Detail:
E-Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Modeler
✨Tip Number 1
Familiarize yourself with AWS services, especially S3 and Redshift, as these are crucial for the role. Understanding how to optimize storage and compute costs in a cloud environment will set you apart from other candidates.
✨Tip Number 2
Brush up on different data modeling methodologies like 3NF, Dimensional, and Data Vault. Being able to discuss these methodologies confidently during your interview will demonstrate your expertise and strategic thinking.
✨Tip Number 3
Prepare examples of past projects where you've successfully managed stakeholder relationships and delivered data modeling solutions. Highlighting your experience in large-scale environments will show that you can handle the demands of this position.
✨Tip Number 4
Stay updated on data governance and ethics, as these are increasingly important in data roles. Being able to discuss how you ensure compliance with standards will make you a more attractive candidate.
We think you need these skills to ace Data Modeler
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description for the Data Modeler position. Understand the key responsibilities and required skills, and think about how your experience aligns with them.
Highlight Relevant Experience: In your CV and cover letter, emphasize your extensive data modeling experience and expertise in methodologies like 3NF, Dimensional, and Data Vault. Provide specific examples of projects where you optimized data designs in cloud environments, particularly AWS.
Showcase Technical Skills: Clearly outline your technical skills related to data design patterns, cloud data warehouses, and data visualization technologies. Mention any relevant qualifications in RDBMS design or AWS architecture to strengthen your application.
Tailor Your Application: Customize your application materials to reflect the language and priorities mentioned in the job description. Use keywords from the listing to demonstrate that you understand the company's needs and can contribute effectively.
How to prepare for a job interview at E-Solutions
✨Showcase Your Data Modeling Expertise
Be prepared to discuss your experience with various data modeling methodologies such as 3NF, Dimensional, and Data Vault. Highlight specific projects where you successfully implemented these methodologies and how they contributed to the overall data strategy.
✨Demonstrate Strategic Thinking
Illustrate your ability to balance storage and compute costs by providing examples of how you've optimized data designs in cloud environments, particularly AWS. Discuss any strategic decisions you've made that improved efficiency in data storage and access.
✨Familiarize Yourself with Data Governance
Understand the principles of data governance and ethics, especially in automated modeling. Be ready to explain how you've ensured compliance with data standards in previous roles and how you would approach this in the new position.
✨Engage with Stakeholders
Prepare to discuss your experience in managing relationships with stakeholders at various levels. Share examples of how you've collaborated with engineering and analytical teams to create backlogs for model standardization and improvements.
