Consultant or Senior Consultant, Snowflake Engineer
Deloitte
As a Snowflake Engineer at Deloitte, you design and deliver scalable, AI-ready data solutions on the Snowflake Data Cloud to support analytics and ML initiatives. You will collaborate with clients and cross-functional teams to translate business needs into reliable data pipelines and data models. Your work strengthens data foundations, optimising performance, security, and governance in complex environments. This role offers hands-on cloud data engineering at scale with a focus on impact and continuous learning.
Pay / Benefits- hybrid working policy
- London base
- growth and development opportunities
- focus on wellbeing
- collaborative culture
- impactful client work
- Engage with technical stakeholders and delivery leads to gather requirements and deliver pipelines aligned with architecture
- Design and implement physical data models covering acquisition, preprocessing, ETL/ELT and deployment
- Support legacy data migrations for on-prem systems with emphasis on scale, efficiency and reliability
- Assess Snowflake technologies and integrate relevant changes into client solutions
- Contribute to knowledge sharing, reusable code and CI/CD practices across sprint teams
- Design, build, test and deploy scalable batch and near-real-time data pipelines and analytics solutions on Snowflake using SQL, Python, Snowpark, Snowpipe, Streams, Tasks and Dynamic Tables
- Manage full data engineering lifecycle from requirements analysis through deployment, operability and improvement
- Communicate solution options, trade-offs and dependencies clearly to technical and non-technical audiences
- Develop robust data models and ETL/ELT patterns supporting analytics, ML and AI use cases
- Optimise pipelines and Snowflake workloads for performance, reliability, scalability and cost with mitigations for engineering risks
- Embed security, RBAC, governance, lineage and data quality using Snowflake features (masking, secure data sharing, account usage views)
- Prepare trusted, governed datasets and integrate data products with downstream applications for analytics and AI
- Apply modern engineering practices including version control, automated testing, CI/CD, IaC, monitoring and data observability
- Produce clear technical artefacts and deployment documentation; participate in technical reviews and establish standards
- Bachelor’s degree in a technical or quantitative field; equivalent acceptable
- SnowPro Core certification (mandatory)
- Experience delivering data solutions in production environments and regulated/data-rich industries
- Experience gathering requirements from business and technical stakeholders and communicating delivery progress
- Strong analytical, problem-solving and troubleshooting abilities
- Experience developing or supporting cloud data warehouses on Snowflake with AWS/Azure/GCP
- Proficiency in SQL, Python, Snowpark, Snowpipe, Streams, Tasks, Dynamic Tables and data stack frameworks
- Knowledge of Snowflake architecture, including stages, file formats, virtual warehouses, secure data sharing, RBAC, Time Travel, cloning and replication
- Experience with query optimisation, warehouse configuration, resource monitors and account usage views
- Experience with CI/CD, IaC, automated testing and coding guardrails; ability to explain technical concepts to diverse audiences
- Ability to build solutions using Snowflake Cortex Code
- Strong understanding of data modelling for analytics, reporting and AI use cases
- Knowledge of cloud-native security, governance and access management; experience enabling AI-ready workloads
- Exposure to DevOps-style tools and Terraform for infrastructure as code
- Experience with orchestration technologies and cloud integration services
- Ability to explain technical concepts clearly and adapt messaging to different audiences
- Collaborative mindset
- Clear communication with both technical and business stakeholders
- Problem-solving orientation and pragmatic approach
- Snowflake architecture and features (Time Travel, cloning, data sharing)
- Snowpark, Snowpipe, Streams, Tasks, Dynamic Tables
- SQL and Python for data engineering
Reference: WJ-747_31054142