About the job
Advansys is an innovative technology solutions provider dedicated to delivering intelligent, modular, and sustainable solutions that enhance operational efficiency, elevate customer experiences, and facilitate business transformation. With a team of over 400 talented engineers, we support more than 100 enterprise clients across 14 countries. Our expertise spans a comprehensive range of premium services, including Business Automation, Industrial Digitization, Low-Code Development, Cloud Services, Warehouse Automation, and Strategic Outsourcing.
Founded in 2014, Advansys operates under the umbrella of the INTRO Group, a well-established private conglomerate since 1980, engaging in various sectors such as oil and gas, real estate, specialized engineering, financial investment, food, and manufacturing.
Job Responsibilities:
- Develop and uphold modeling standards, guidelines, best practices, and approved methodologies.
- Oversee the creation and governance of all physical and logical data models within the organization.
- Engage in the evaluation of new software acquisitions by reviewing proposed data models within packaged or commercially available applications.
- Participate in data integration, business intelligence, and content management teams.
- Contribute to data integration and Enterprise Information Management (EIM) initiatives by streamlining data processing for reusable module development.
- Collaborate with the data services administrator to create data objects and models supporting data services under a service-oriented architecture.
- Lead the data administration team, focusing on modeling, metadata management, and user query optimization.
- Coordinate with the data modeling team, data warehouse team, and application owners to clarify data interface requirements and assist project developers in resolving data-related issues, ensuring effective management of gatekeeper functions to reduce redundancy and enhance data accuracy.
- Assist in selecting data management tools and developing standards, guidelines, and procedures for their use.
- Document the current data architecture to maintain an accurate ‘as is’ view and define the desired ‘to be’ state.
- Visualize data flows and lineage to illustrate current data movement across key data landscape components and define future states.
- Collaborate with various technology and business stakeholders to address and escalate issues regarding data solutions, ensuring alignment and approval throughout the software development life cycle until deployment.
- Provide constructive feedback and suggestions for improving standards and methodologies.
