Data Engineering - Solution Architect (Snowflake, AWS))

Company Description

MResult is a leading data & analytics intelligence technology solutions provider with a focus on helping companies monetize their data assets and generate real-time actionable insights. We offer technology-enabled solutions and services in data, analytics, and AI to drive growth and optimize business operations. Trusted by Fortune 500 companies and start-ups, we bring together domain expertise, analytics capabilities, and innovative AI to deliver world-class solutions.

Role Description

We are looking for a highly motivated individual to join our team having strong Data Engineering/Solution Architecture experience.

1.

Architect and Implement Solutions: Design and deploy scalable, high-performance data architectures using Snowflake, DBT, PL/SQL, Python, and AWS cloud solutions.

2.

Data Integration Leadership: Lead the integration of diverse data sources, ensuring seamless data ingestion, transformation, and storage on AWS cloud platforms.

3.

Database Optimization: Optimize existing database systems for performance, reliability, and scalability, leveraging AWS services where applicable.

4.

Technical Expertise: Provide deep technical expertise and innovative solutions to complex data challenges, incorporating AWS cloud technologies.

5.

AWS Solutioning: Develop and implement cloud-based data solutions using AWS services such as S3, Redshift, RDS, Lambda, and Glue.

6.

Collaboration: Work closely with data engineers, data scientists, and business stakeholders to align data solutions with business goals, utilizing AWS cloud infrastructure.

7.

Documentation: Develop and maintain comprehensive technical documentation for all data architecture and solutions, including AWS cloud components.

8.

Mentorship: Mentor junior team members, fostering a culture of learning and continuous improvement, with a focus on AWS cloud best practices.

9.

Best Practices: Implement and advocate for best practices in data engineering, including coding standards, testing, data governance, and cloud security.

10.

Performance Monitoring: Monitor and enhance data processing workflows to ensure optimal performance and efficiency, leveraging AWS monitoring tools such as CloudWatch.

11.

• Stakeholder Communication: Effectively communicate technical concepts and project status to non-technical stakeholders and executive management, including the benefits of AWS cloud solutions.