Key skills
AirflowAWSAzureCloudETLGoogle Cloud PlatformMatillionSQLELTData EngineeringData WarehousingAnalyticsSnowflakedbtFivetranGCPGoogle CloudAgile
About this role
Role Overview
- 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.
- 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.
- Monitor Snowflake usage, query performance, and cost consumption to drive optimisation initiatives.
- Support data lifecycle management, retention, and governance policies within Snowflake.
- Enable self-service analytics capabilities through well-structured semantic layers and governed datasets.
- Collaborate closely with Product, Engineering, Operations, Finance, and Business stakeholders to deliver impactful data solutions.
Requirements
- 5+ years of experience in Data Engineering, Analytics Engineering, or related data platform roles.
- Experience designing and supporting multi-region and enterprise-scale data platform architectures.
- Strong experience driving performance optimisation and cloud cost efficiency initiatives across large-scale data workloads.
- Strong understanding of platform reliability, operational maturity, resilience, and production support practices.
- Experience implementing advanced governance, security, access control, and data protection models within enterprise data platforms.
- Strong capability in developing architectural standards, engineering documentation, and scalable platform design patterns.
- Strong hands-on expertise with Snowflake in enterprise-scale environments.
- Advanced SQL skills with experience optimising complex analytical queries and data transformations.
- Strong experience building and maintaining modern ELT/ETL pipelines and orchestration workflows.
- Strong understanding of modern data warehousing concepts, dimensional modelling, and scalable data architecture.
- Experience working with cloud platforms such as AWS, Azure, or GCP.
- Experience with data transformation and orchestration tools such as dbt, Airflow, Fivetran, Matillion, or equivalent platforms.
- Experience integrating structured and semi-structured data sources.
- Strong understanding of data governance, security, and access management principles.
- Proven ability to manage large and complex datasets in production environments.
- Strong analytical, troubleshooting, and problem-solving capabilities.
- Ability to work effectively in fast-paced, agile, and collaborative environments.
Tech Stack
- Airflow
- AWS
- Azure
- Cloud
- ETL
- Google Cloud Platform
- Matillion
- SQL
Benefits
- ZigZag is committed to building a diverse, inclusive, and equitable workplace.
- We welcome individuals from all backgrounds.
- Guided by transparency and agility, we foster an environment where everyone is valued and empowered to thrive.