Solution Architect - Data & AI

Responsibilities:

• Solution Design: Collaborate with cross-functional teams to gather requirements, design end-to-end data analytics solutions, and create architectural diagrams and documentation.
• AWS Expertise: Leverage your extensive knowledge of AWS services such as Amazon Redshift, Amazon EMR, Amazon Kinesis, AWS Glue, and others to architect robust data analytics platforms.
• Data Modeling: Design and optimize data models to support reporting, analytics, and business intelligence needs while ensuring data integrity and performance.
• Scalability and Performance: Architect solutions that are scalable, high-performing, and cost-efficient, considering factors like data volume, query complexity, and user concurrency.
• Data Integration: Define data integration strategies to extract, transform, and load (ETL) data from various sources into the analytics platform, ensuring data consistency and quality.
• Security and Compliance: Implement security measures and best practices to protect sensitive data and ensure compliance with industry standards and regulations.
• Troubleshooting and Optimization: Identify and resolve performance bottlenecks, data quality issues, and other challenges that may arise during implementation and operation.
• Collaboration: Work closely with data engineers, data scientists, business analysts, and stakeholders to understand their needs and provide technical guidance.
• Innovation: Stay up-to-date with industry trends and emerging technologies to recommend innovative solutions that enhance our data analytics capabilities.

Job Requirements Skills

• Proven experience (3+ years) as a Solution Architect or similar role, with a focus on data analytics and AWS cloud technologies.
• Extensive hands-on experience with AWS services such as Amazon Redshift, Amazon EMR, Amazon Kinesis, AWS Glue or AWS quick sight etc.
• Strong understanding of data modeling, ETL processes, data warehousing, and data governance principles.
• Familiarity with programming/scripting languages like Python, SQL, and experience with data manipulation and transformation.
• Excellent problem-solving skills with the ability to design and implement creative solutions for complex data challenges.
• Strong communication skills to effectively collaborate with technical and non-technical teams.
• Experience in working with Agile methodologies and version control systems.
• Proven ability to work independently and manage multiple priorities effectively.