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.
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