Data Architect

Brain Ridge Consulting is a premium Fin Tech Technology Consulting firm with the energy of a startup and experience of an enterprise. With a mission to empower financial institutions and organizations to thrive in the digital age, we provide cutting-edge technology solutions and strategic guidance to drive innovation and growth. As we continue to grow, we are seeking a motivated and experienced Data Architect.

Brain Ridge Consulting is seeking a visionary and experienced Data Architect to lead the design and governance of our clients' modern data ecosystems.
Responsibilities   Define and own the overall data architecture strategy across cloud and on-prem environments, ensuring scalability, performance, and security
Design and implement enterprise-grade data models, schemas, and integration frameworks leveraging AWS and Snowflake
Partner with cross-functional business and technology leaders to align data architecture decisions with core business goals and analytics initiatives
Evaluate and select appropriate technologies and tools for data ingestion, storage, management, and analytics
Establish and enforce architectural standards, best practices, and governance frameworks across the data lifecycle
Drive optimization of Snowflake and AWS data environments for performance, cost efficiency, and reliability
Collaborate with data engineering teams to implement Data Ops practices, including CI/CD, automation, and observability
Provide architectural oversight and mentorship to data engineering teams, supporting solution design and technical reviews
Lead enterprise data migration, integration, and modernization initiatives, ensuring quality, compliance, and continuity
Champion data governance, metadata management, and access control policies to safeguard enterprise data assets
Qualifications   8-12 years of experience in data architecture, data engineering, or BI solution design within large-scale or enterprise environments
Deep expertise in Snowflake (architecture, performance tuning, data sharing, and governance) and the AWS data ecosystem (S3, Glue, Lambda, Redshift, IAM)
Strong background in designing data models, data lakes, and analytical warehouses for large-scale analytics workloads
Proficiency in SQL and familiarity with Python or Java for architectural prototyping and automation
Experience implementing Data Ops and modern data stack components (dbt, Airflow, or similar orchestration frameworks)
Proven leadership in designing and implementing complex data strategies, migrations, or cloud modernization initiatives
Excellent stakeholder management and communication skills; ability to translate business needs into technical architecture
Strong analytical mindset and knowledge of data governance, security, and compliance frameworks