Data Solution Architect
We are seeking a Data Solution Architect to design and drive lots of solutions that generate value from data, taking advantage of scalable platforms, cutting-edge technologies and machine learning algorithms.
In this role, you will be empowering the organization's digital transformation through enterprise data enablement.
Responsibilities
- Address organization business goals and strategy using best practices in business-, enterprise-, solution-, data architectures, as well as in software engineering
- Analyze business problems and technology landscape, identify significant requirements and design solutions
- Perform hands-on software engineering with creation of data models and code review
- Build data management environments (data platforms), where data and AI products can be produced and hosted, both on-premises and in the cloud, considering security, compliance and regulatory limitations
- Report data flow, data quality metrics and operational statuses
- Guide team efforts in integration and harmonization of data from different sources, building analytical data tools
- Manage data products life cycle end-to-end, ensuring their data quality, security and privacy
- Drive data technology consulting services, helping clients shape a vision of the solution and make decisions under uncertainty
Requirements
- 7+ years of experience in solution architecture, engineering, systems development, deployment and maintenance
- Knowledge of architecture, design patterns and technological landscape in at least 3 technology domains (Data Platforms, IoT, ML, Backend, Mobile, etc.)
- Solid understanding of the core concepts in data and analytics platform architectures, data warehousing, business intelligence, data management, integration, security and operations areas
- Wide experience in design, implementation, deployment, troubleshooting and re-platforming of distributed systems both on premises and in the cloud
- Structured and systematic knowledge of the entire architecture design process (requirements, quality attributes, technology selection, estimation, proposal verification, documentation, etc.)
- Solid background in all phases of the software development life cycle using different development methodologies and best practices
- Well-developed communication and presentation skills
- C1+ English level
