Data Engineer (Snowflake)

<p><strong>Role Overview</strong></p><p>We are modernising an enterprise data warehouse into a cloud-native analytics platform on AWS and Snowflake. We are seeking a <strong>Senior / Lead Data Engineer</strong> to design and deliver reliable ingestion and ELT pipelines, dimensional data models, and production-grade operational controls.</p><p>This is a hands-on role with scope to lead technical direction, mentor engineers, and work closely with architects, QA, and platform teams across build, testing, and go-live phases.</p><p><br></p><p><strong>Key Responsibilities</strong></p><ul><li>Design and build scalable data pipelines and warehouse layers in <strong>Snowflake (RAW / ODS / DW schemas, tables, views).</strong></li><li>Implement ingestion and orchestration using Snowflake capabilities such as Stages, Storage Integrations, Snowpipe, Tasks, Streams, and Stored Procedures (or agreed equivalent patterns).</li><li>Develop and maintain dimensional data models (facts and dimensions), including transformations, aggregates, and performance optimisation.</li><li>Implement data quality checks, reconciliation processes, and validation controls to ensure data accuracy and consistency.</li><li>Build production-ready operational controls including error handling, rerun/recovery patterns, monitoring support, and clear runbooks/documentation.</li><li>Collaborate with cloud/DevOps, QA, and BI/reporting teams; support SIT, UAT, and deployment activities.</li></ul><p><br></p><p><strong>Qualifications</strong></p><p><strong>Must-Have Requirements</strong></p><ul><li>5+ years of experience in data engineering and enterprise data warehousing delivery.</li><li>Strong SQL expertise, including complex joins, window functions, and performance tuning.</li><li>Hands-on experience with Snowflake, or strong cloud data warehouse experience with the ability to ramp up quickly.</li><li>Solid understanding of dimensional modelling (fact and dimension design).</li><li>Experience with cloud data integration patterns (e.g., S3 or similar object storage).</li><li>Familiarity with production pipeline practices such as logging, retries, and operational support.</li></ul><p><br></p><p><strong>Plus Points (Advantage)</strong></p><ul><li>Experience migrating Oracle or other legacy data warehouses to cloud platforms.</li><li>Handling of semi-structured data (JSON, XML, VARIANT).</li><li>CI/CD for data platforms (Git-based workflows, automated deployments).</li><li>Exposure to BI tools (e.g., Tableau) and governed dataset publishing.</li><li>AI / ML / GenAI-related certifications.</li></ul><p><br></p><p><strong>What We Value</strong></p><ul><li>Strong ownership mindset and practical problem-solving skills.</li><li>Sound engineering fundamentals and clean, maintainable implementations.</li><li>Ability to work effectively in fast-paced, delivery-driven environments.</li><li>Willingness to learn and adapt — a perfect 100% skill match is not required.</li></ul><p><br></p><p><strong>Senior / Lead Expectations</strong></p><ul><li>Ownership of a data workstream end-to-end.</li><li>Ability to guide technical design decisions and review peer deliverables.</li><li>Comfortable engaging stakeholders to clarify requirements and deliver iteratively.</li></ul><p></p>