Data Modeller Manager

About Mindvalley

Mindvalley is the leading and most promising ed-tech company to date. We dominate the US market for Personal Growth Education. We are empowering athletes within every major US sports team and promoting successful learning strategies in major companies.

We're currently building the most advanced learning system - a version inspired by Ironman's “J.A.R.V.I.S.” which utilizes AI and augmented reality to provide customised learning. Turning anyone into a superhero.

We innovate tools that induce enlightenment within every aspect of human life. We are seeking the best engineers to build the best and most advanced education platform our species has seen. The goal to mark our success is: powering up to 100 countries, powering every Fortune 500 company, and progressing humanity towards a better future.

About The Role

The Mindvalley data engineering and Analytics teams are helping to build the future of education through data-informed decision making and data-powered products.

We are looking for an exceptional Data Modeller to design and implement data modeling solutions using relational and dimensional databases. As a data modeler, you will be working closely with data engineers and data analysts to implement data modeling solutions to streamline and support information management. To ensure success as a data modeler, you should have in-depth knowledge of data warehousing, pipelines and schema. Ultimately, you will be designing models to reduce data redundancy, streamline data movements and improve Mindvalley’s information management.

Responsibilities

• Analyze source system data. Understand how they relate. Understand how each system is used by various groups in the organization and how that impacts the life cycle of the data
• Assess the quality of company data. Identify data quality issues in our master and reference data and work with subject matter experts - Analysts, Data Engineers and IT to remediate these data problems
• Document current state of data and data repositories. Build business glossaries and data dictionaries as well as entity diagrams
• Partner with Analytics to interview end users to better understand their metrics and KPIs
• Document these definitions and map them to source system data elements
• Create source target mappings between source systems and the newly modeled warehouse These mappings should explain how data should be transformed to fit the new models
• Design and maintain data models continuously as modifications and enhancements are made
• Create conceptual, logical and physical data models for reporting and analytics solution
• Create entity-relationship diagrams for relational systems and dimensional diagrams
• Create data models using Star-Schema modelling techniques
• Define and employ data modeling and design standards, tools, best practices, and related development methodologies
• Manages the life cycle of the data model from requirements to design to implementation to maintenance
• Identify areas where data can be used to improve business activities
• Work with the Data Engineers to help ensure that the business data rules are implemented correctly and create optimal physical data models of datasets
• Experience in Maintaining a model repository considering the frequent changes in the system
• Evaluate existing data models and physical databases for variances and discrepancies
• Developing, publish and maintain all documentation for data models
• Experience in Synchronizing models to ensure that database structures match models
• Educate IT and business teams on the models created for analytical and transactional purposes
• Work with analytics, data engineers, application developers and technical architect to understand data landscape, data sources, database constraints and implementation considerations
• Serve as a fully seasoned and proficient technical resource - should be ready to get into the weeds of the code, analyze and research data problems and discuss technical details with the IT Development team and Analytics
• Support the analytics by helping to find hidden insights and connections within the data

Qualifications

• Bachelor’s degree in a quantitative field of Computing or Computer Science
• 5+ years experience in database modeling / cloud data warehouse architecture
• 5+ years experience in data modelling or extensive BI pipeline experience
• Experience in data / analytics project implementations
• 5+ years experience with ETL design and development tools
• 5+ years experience with ERwin Data Modeler tools
• Strong hands on experience with SQL and at least one scripting language (e.g. Python)
• Understanding of data from Google, Facebook, Google Analytics, Firebase, Mixpanel
• Experience in managing and implementing successful projects
• Working knowledge of consulting/project management techniques/methods
• Ability to work under pressure and manage deadlines or unexpected changes in expectations or requirements
• Demonstrated experience creating conceptual, logical and physical models (ERD, normalized and dimensional models)
• Previous experience with metadata management strategies and implementation
• Demonstrates expertise in a variety of data warehousing and business intelligence concepts, practices, and procedures
• Previous experience conducting requirements gathering and design sessions with stakeholders
• Experience producing written deliverable for technical designs
• Understanding of indexing and data design performance considerations for industry standard DBMS
• Ability to design, organize, and implement module, perform system testing, plan and automate tasks to maintain existing systems
• Ability to research and trouble-shoot SQL problems
  
  

Other Skills 

• Ability to work creatively and analytically in a problem-solving environment
• Excellent leadership, communication (written and oral) and interpersonal skills
• Excellent problem solving skills and like new challenges
• Contribute and enhance the improvement require for existing process
• Customer service oriented mindset and able to assess impact of operational problem and advice relevant mitigation
• Good understanding of the end to end value chain, both technical and business
• Team player, responsible, reliable, and take ownership until task are fully completed end to end
• Eagerness to contribute in a team-oriented environment
• Ability to balance multiple demands and work both independently and as part of a team to develop solutions