Join our dynamic Technology & Transformation practice, where you'll help clients harness the power of their data. This role focuses on uncovering and unlocking value from vast data sources, providing strategic guidance and implementation services. You'll work with business intelligence, data management, and advanced analytics, including cloud, cognitive, and machine learning technologies.

As a Senior Consultant in Snowflake Quality Engineering, you will be instrumental in managing client relationships and ensuring the successful delivery of data engineering programs. You'll be the main liaison between our organization and clients, aligning goals, timelines, budgets, and deliverables while driving satisfaction and business growth.

Own the end-to-end technical design and implementation of complex Snowflake data solutions. This includes designing robust ELT/ETL pipelines for various data types and implementing Snowflake's advanced features. You will establish reusable data engineering patterns, frameworks, and quality code standards. Lead advanced data modeling efforts and engineer secure integrations across Snowflake and major cloud platforms (AWS, Azure, GCP).

Drive query and workload optimization for performance and cost efficiency. Define and implement production-grade observability, data quality, and governance controls. Set up platform security and access management patterns. Lead code reviews, technical design sessions, and CI/CD implementation. Mentor engineers, resolve complex technical challenges, and contribute to planning and risk management.

We are seeking experienced professionals with 5 to 8 years of hands-on experience delivering production-grade Snowflake platforms and enterprise-scale data engineering solutions. Advanced SQL expertise for complex transformations and performance optimization is crucial. Strong Python engineering skills for building reusable components and automation are required.

Demonstrated experience with ELT/ETL tools (e.g., dbt, Airflow, Informatica) and at least one major cloud ecosystem (AWS, Azure, GCP) is essential. Proven capability in data modeling, incremental processing, schema evolution, data quality, and production support is expected. Experience with CI/CD, automated testing, Git, and infrastructure as code is also necessary.

Ability to lead technical discussions, communicate risks, and guide engineering teams through complex challenges is key. Familiarity with Snowflake cost governance, performance features, and advanced platform patterns is advantageous. Working knowledge of data governance, privacy controls, and exposure to AI/ML data platforms are desirable. Banking and Financial Services experience is a plus, as are SnowPro Advanced or relevant cloud/data engineering certifications.