Sr Data Engineer (Snowflake) | Dayshift | Remote

ZigZag is looking for a **Sr Data Engineer** to join our team! # **About the role** We are seeking an experienced Senior Data Engineer to design, build, and scale modern cloud-based data platforms that enable trusted analytics, operational reporting, and data driven decision making across the organisation. This role will play a critical part in evolving our data architecture, data engineering practices, and analytics capabilities, with a strong focus on Snowflake as the core enterprise data platform. As a senior member of the data team, you will be responsible for building robust and scalable data pipelines, optimising data models, improving data quality and governance, and enabling self-service analytics capabilities for business and engineering stakeholders. The ideal candidate combines strong technical depth in modern data engineering practices with a pragmatic mindset, excellent stakeholder engagement skills, and a passion for building reliable and scalable data platforms. **Data Platform & Engineering** - Design, build, and maintain scalable and secure cloud-native data platforms and data pipelines. - Lead the architecture, optimisation, and operational management of the Snowflake data warehouse platform. - Develop robust ELT/ETL pipelines to ingest, transform, and deliver high-quality data from multiple internal and external sources. - Build reusable and maintainable data frameworks, transformation models, and orchestration workflows. - Develop and maintain infrastructure-as-code and automation for data platform provisioning and management where appropriate. - Optimise performance, scalability, and cost efficiency across data storage, transformation, and query workloads. - Support near real-time and batch-based data processing requirements. **Snowflake Engineering & Optimisation** - Own and continuously improve Snowflake architecture, performance tuning, security, governance, and operational best practices. - Design and optimise Snowflake schemas, warehouses, clustering strategies, and data sharing capabilities. - Implement scalable data modelling approaches including dimensional modelling and data vault methodologies where appropriate. - Manage Snowflake access controls, roles, permissions, and secure data sharing practices. - Monitor Snowflake usage, query performance, and cost consumption to drive optimisation initiatives. - Support data lifecycle management, retention, and governance policies within Snowflake. **Data Modelling & Analytics Enablement** - Design and maintain curated, trusted, and scalable data models to support analytics, reporting, and operational use cases. - Partner with analysts, business stakeholders, and engineering teams to translate business requirements into scalable data solutions. - Enable self-service analytics capabilities through well-structured semantic layers and governed datasets. - Support and optimise BI and reporting platforms such as Looker, Power BI, or equivalent tools. - Ensure data structures and models support both operational reporting and strategic analytics requirements. **Data Quality, Governance & Reliability** - Implement data quality controls, validation frameworks, reconciliation processes, and monitoring capabilities. - Proactively identify and resolve data integrity, consistency, and performance issues. - Establish observability and operational monitoring for data pipelines and platform reliability. - Contribute to data governance, lineage, cataloguing, and metadata management practices. - Ensure data platforms and engineering processes comply with security, privacy, and regulatory requirements. **Collaboration & Leadership** - Collaborate closely with Product, Engineering, Operations, Finance, and Business stakeholders to deliver impactful data solutions. - Mentor and support junior engineers and analysts within the broader data function. - Contribute to data engineering standards, best practices, and platform strategy. - Drive continuous improvement initiatives ac…