Senior Data Engineer (Snowflake)
- Compensation
- Not disclosed
- Location
- Philippines
- Work setup
- Onsite
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data engineering
- Posted
Skills
Nice to have
- Experience within fintech, payments, SaaS, or highly regulated industries.
- Experience with real-time data streaming technologies such as Kafka or Kinesis.
- Exposure to machine learning data pipelines and advanced analytics workloads.
- Experience implementing CI/CD practices for data engineering workflows.
- Familiarity with Infrastructure-as-Code tools such as Terraform.
- Experience with data observability and quality tooling.
- Exposure to compliance frameworks such as PCI-DSS, ISO27001, or SOC 2.
- Experience mentoring engineers or leading technical initiatives
Full description
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.