The Data Solutions Architect provides technical expertise in the analysis, design, and development of enterprise architecture, data models, and solutions. This role works closely with project teams to ensure successful client engagements and leads client assessments, delivering future-state architectures and recommendations.
Key Responsibilities:
- Lead technical teams in designing and implementing technical solutions for business problems.
- Create and communicate end-to-end solutions for clients after thorough evaluations of current needs.
- Design and develop conceptual, logical, and physical data models for large-scale data lake and data warehouse solutions.
- Perform technical feasibility assessments and POC development for cloud migrations.
- Review and implement enterprise data management architectures in AWS.
- Collaborate with business users to analyze and test requirements, while staying current with emerging technologies.
- Develop migration approaches to move workloads to the Cloud or create cloud-ready applications.
- Ensure data integration processes using tools like Databricks, Glue, Data Factory, and others.
- Document functional and technical requirements such as data models, integration specifications, and testing plans.
- Support practice leads in strategy development and client assessments.
Education & Experience:
- Bachelor’s or Master’s degree in Business or IT or 5+ years of relevant professional experience.
- 10+ years of experience in Business Intelligence/Data Warehouse implementations, with 4+ years in technical or solution architecture in AWS.
- 3-5 years of experience in enterprise data modelling.
- Experience with data modelling tools like ERwin, ER/Studio, or Power Designer.
- Familiarity with database platforms such as Oracle, SQL Server, and Teradata.
Preferred Skills & Experience:
- Experience with Big Data technologies and Cloud platforms (IaaS/PaaS/SaaS).
- Hands-on experience in integrating multiple databases and familiarity with cloud deployment technologies.
- Knowledge of CI/CD tools like AWS DevOps and Terraform, and experience with Kubernetes and Docker.
- Strong background in business intelligence, data governance, and data warehouse concepts.
- Experience in leading project teams and working with both waterfall and agile development methodologies.
