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