Senior Data Engineer

Role Description

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
• 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.

Qualifications

• 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
• Excellent communication and stakeholder engagement skills
• Ability to work effectively in fast-paced, agile, and collaborative environments

Requirements

• Experience within fintech, payments, SaaS, or highly regulated industries (Desirable)
• Experience with real-time data streaming technologies such as Kafka or Kinesis (Desirable)
• Exposure to machine learning data pipelines and advanced analytics workloads (Desirable)
• Experience implementing CI/CD practices for data engineering workflows (Desirable)
• Familiarity with Infrastructure-as-Code tools such as Terraform (Desirable)
• Experience with data observability and quality tooling (Desirable)
• Exposure to compliance frameworks such as PCI-DSS, ISO27001, or SOC 2 (Desirable)
• Experience mentoring engineers or leading technical initiatives (Desirable)

Benefits

• ZigZag is committed to building a diverse, inclusive, and equitable workplace
• We believe that talent knows no borders, and we welcome individuals from all backgrounds
• Guided by transparency and agility, we foster an environment where everyone is valued and empowered to thrive