Data Engineer

Duties and Responsibilities:

• Data Platform Delivery (Snowflake + Azure)
• Build and maintain ELT pipelines and transformations in Snowflake, with a strong focus on SQL quality and performance
• Develop and optimise Snowflake stored procedures / SQL-based transformations aligned to engineering standards
• Work within an Azure-based ecosystem and contribute to secure, reliable pipeline operations
• Data Vault 2.0 Modelling and Implementation  
• Design and implement Data Vault 2.0 structures (Hubs, Links, Satellites), including business vault logic where required
• Re-model legacy reporting data into scalable, auditable Data Vault patterns
• Collaborate with architects and domain experts to interpret and codify business rules—especially where rules differ across legacy systems
• Reporting and Delivery Enablement 
• Create and maintain reporting-ready layers (e.g., information marts / dimensional patterns where appropriate) to support Power BI
• Support new delivery methods such as Power Automate outputs for end users where required 
• Data Ingestion & Orchestration 
• Work with ingestion patterns where source data lands as Parquet (e.g., delta/Parquet structured files)
• Use and support orchestration via Azure Data Factory (ADF)—especially for onboarding new sources and maintaining reliable workflows 
• Project Delivery  
• Operate in an Agile delivery environment (e.g., Jira / Scrum), contributing to sprint planning, estimation, and continuous improvement
• Participate in peer reviews and knowledge sharing to uplift capability across the team 

Required Experience/Skills :

• Required Skills:
• Strong experience as a Data Engineer delivering enterprise data platforms and pipelines
• 4 -5 years of experience in a similar capacity or in Data Engineer roles
• Demonstrated capability with Data Vault 2.0 (modelling + implementation)
• Strong SQL skills (complex transformations, performance tuning, procedural logic)
• Hands-on experience with Snowflake and the ability to further ramp up your proficiency using your strong SQL foundations 
• Experience working with cloud data ecosystems (ideally Azure)
• Ability to translate business/reporting requirements into scalable data models and transformations
• Desirable Skills:
• Experience with Azure Data Factory (ADF)
• Familiarity with Parquet / delta-style file-based ingestion patterns.
• Experience building reporting layers/information marts and/or dimensional modelling
• Exposure to Data Vault tooling such as IRIS (or similar modelling/automation tools).
• Experience with CI/CD / DevOps practices for data engineering 
• Certifications:
• Data Vault 2.0 certification mandatory
• Snowflake certification is desirable
• Azure fundamentals certification is desirable