We are seeking a highly skilled Snowflake DBA / Snowflake Architect to join our EMEA Data Solutions domain. In this strategic role, you will be responsible for designing, implementing, administering, and optimizing Snowflake‑based data platforms that support our enterprise analytics, data engineering, and AI‑driven initiatives. You will collaborate closely with cross‑functional teams to ensure high availability, performance, governance, and security across our Snowflake environment, while enabling scalable, cost‑efficient, and reliable data solutions.
Key Responsibilities
Architecture, Design & Administration
- Design, implement, and maintain scalable, secure, and high‑performance Snowflake architectures, including virtual warehouses, databases, schemas, roles, and resource monitors.
- Develop, manage, and optimize Snowflake compute, storage, and workload patterns to ensure cost‑efficient operations aligned with business requirements.
- Oversee data sharing, replication, failover, and cross‑region strategies for resiliency and disaster recovery.
Performance, Optimization & Operations
- Monitor and tune query performance, workload management, and compute resource allocation to ensure SLAs are met.
- Implement Snowflake best practices for performance, cost governance, and system scalability.
- Troubleshoot operational issues across Snowflake workloads, data pipelines, integrations, and user environments.
Data Integration, Modeling & Transformation
- Work with data engineering teams to optimize ELT pipelines feeding Snowflake from upstream tools (e.g., StreamSets, Informatica, Airflow, DBT, Kafka).
- Provide expertise on data modeling (Kimball, Inmon, Data Vault) and implement efficient table designs, clustering keys, file formats, and micro‑partitioning strategies.
- Support downstream analytics, BI, and AI workloads by ensuring high‑quality data structures and efficient query access.
Governance, Security & Compliance
- Implement and enforce Snowflake security models, including RBAC, access policies, network policies, and masking/column‑level security.
- Manage data replication, failover, and disaster recovery strategies to uphold RPO/RTO commitments.
- Ensure compliance with organizational standards and governance principles across the Snowflake environment.
- Maintain complete operational documentation, including architecture diagrams, configuration details, and operational runbooks.
Collaboration & Continuous Improvement
- Partner with architecture, engineering, analytics, and platform teams to define Snowflake standards, patterns, and reusable frameworks.
- Evaluate and recommend new Snowflake features, integrations, and ecosystem tools to improve platform capabilities.
- Provide observability, production support, root-cause analysis, proactive issue resolution, and preventative improvements for Snowflake workloads and integrations.
Technical Qualifications
- 7+ years of experience in data engineering, data warehousing, or database administration in an enterprise environment.
- Hands‑on expertise in Snowflake administration, architecture, performance tuning, and cost governance.
- Understanding of SQL and data transformation frameworks, i.e., DBT and Airflow.
- Understanding data ingestion and ETL/ELT tools, such as StreamSets, Informatica, Kafka, and similar technologies.
- Knowledge of AWS services relevant to analytics and Snowflake deployments (IAM, S3, Lambda, EKS, EMR, MWAA, Lakehouse/Iceberg).
- Understanding of data modelling methodologies: Kimball, Inmon, Data Vault, and normalized/denormalized modeling patterns.
- Understanding of CI/CD and IaC using Terraform, CloudFormation, GitHub Actions, or similar.
- Familiarity with monitoring and APM tools for data and platform observability.
- Understanding of software architecture patterns, distributed systems, and cloud-native design principles.
Non‑Technical Skills
- Strong analytical and diagnostic skills with attention to detail.
- Ability to work proactively, identifying issues and proposing effective solutions before they impact business operations.
- Excellent communication skills, able to convey complex technical content clearly to technical and non‑technical stakeholders.
- Passion for innovation and continuous learning, especially in cloud data platforms and modern data ecosystem tools.
- AI Empowered Experience.