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Data Solution Architect

2 months ago

London, Greater London, United Kingdom FalconSmartIT Full time

Job Title: Data Solution Architect

Job Type: Full-time / Permanent

Job Description:

Key Responsibilities:

1. Lead the development of data technology strategies and solutions for FalconSmartIT's clients, leveraging expertise in data technologies and applications.

2. Collaborate with business stakeholders to understand client needs and provide holistic solutions that integrate data and AI capabilities.

3. Conduct data landscape assessments, portfolio rationalization, and provide solutions to modernize, migrate, and integrate applications on hyperscalers using best practices.

4. Engage with technology stakeholders to gather information, understand client expectations, and provide subject matter expertise to resolve business issues.

5. Design enterprise data platforms on cloud (Azure/AWS/GCP) including services like ETL pipelines, data modeling, visualization, data governance, RDM/MDM, etc.

Requirements:

1. A balanced mix of technical and business skills, with experience working with an enterprise architecture team for strategic direction.

2. Develop and drive domain/application standards and best practices that align with enterprise direction.

3. Proven work experience as a Data Solution Architect or similar role in building data architecture, data models, pipelines using AWS services (S3, Lambda, Glue, Athena, QuickSight, etc.) or similar native Azure or GCP services.

4. Strong experience on Snowflake or DataBricks (including PySpark) along with tools like DBT or Snaplogic or Informatica Stack.

5. Proactively seek to understand major industry trends and apply them to solutions, new initiatives, and capability roadmaps.

6. Provide technical guidance to project teams and work closely with other architects to ensure project architectures follow established architecture standards and guidelines.

7. Good communication and presentation skills, with the ability to understand business priorities and how technology can support these initiatives.

8. Understanding of Agile-based development and execution approaches.

9. Well-versed with data consumption design patterns like semantic layers, visualizations, ML models, etc.