• Platform Leadership: Design, implement, and manage Snowflake as the enterprise data hub, ensuring scalability, security, and performance.
• Data Architecture & Strategy: Define frameworks for ingestion, replication, storage, and transformation across diverse data sources.
• Pipeline Development: Build efficient ELT pipelines using tools such as DBT and Python, integrating operational, financial, and network data.
• Performance Optimisation: Configure Snowflake warehouses and partitioning strategies for cost efficiency and speed.
• Governance & Compliance: Implement data quality, lineage, and access control aligned with regulatory and security standards.
• Innovation: Drive adoption of advanced Snowflake features (Snowpark, Streams, Tasks, Secure Data Sharing) to enhance platform capabilities.
• Mentorship: Guide and develop data engineers and analysts in best practices and technical excellence.
• Stakeholder Collaboration: Work closely with business teams to deliver scalable data products for analytics and emerging ML initiatives.
• Monitoring & Reliability: Establish monitoring, alerting, and cost management strategies to ensure resilience and predictable spend.

• Proven experience designing and delivering cloud-based data platforms at scale (Snowflake preferred).
• Expertise in cloud data architecture, including data lakes, lakehouses, and warehouse design.
• Advanced proficiency in SQL, DBT, and Python for ELT workflows.
• Hands-on experience with Snowflake features: schema design, micro-partitioning, warehouses, tasks, streams, and Snowpark.
• Familiarity with replication and transformation tools (Airbyte, DBT) and cloud ecosystems (AWS preferred).
• Strong understanding of data governance, metadata, and lineage frameworks.
• Experience enabling BI tools (e.g., Power BI) through Snowflake data models.
• Desirable: Experience in data migration, change management, and enterprise rollout of modern data platforms.

What you need to do now

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