Intermediate Data Engineer at Ignition Group

Description

Data Pipeline Development and Optimisation

• Build, maintain, and optimise robust, production-grade data pipelines using Snowflake and modern orchestration tools. 
• Implement data transformations, ingestion, and integration across multiple sources (CRM, WFM, Telephony, Digital). 
• Builds production-grade pipelines with orchestration 
• Apply Snowflake best practices for warehouse design, schema structuring, and performance tuning. 

 Automation and Orchestration

• Integrate Cortex Agents or similar automation tools to streamline data workflows. 
• Implement and maintain ETL/ELT orchestration using tools such as Airflow or dbt. 
• Implements automated workflows and test. 
• Implements data tests and monitoring 
• Automate repeatable processes to enhance reliability and scalability. 

Data Quality, Lineage, and Governance

• Apply data quality checks, lineage tracing, and validation rules to ensure data accuracy and consistency.
• Document data processes, pipelines, and source-to-target mappings for transparency and maintenance.
• Implements RBAC and lineage documentation.
• Support adherence to organisational data governance and compliance standards.

Data Modelling and Analytics Enablement

• Design and maintain analytical data models and structures for business reporting and dashboards. 
• Work closely with analysts and business partners to translate KPIs into well-defined data structures. 
• Ensure data is structured to support contact centre KPIs such as AHT, FCR, NPS, occupancy, and SLA. 

Collaboration and Technical Contribution

• Collaborate cross-functionally with Senior Data Engineers and Data Architects to improve performance and reliability. 
• Participate in peer reviews, design sessions, and technical documentation activities. 
• Contribute to continuous improvement initiatives and knowledge sharing across the team. 

Continuous Learning

• Stay current with advancements in data engineering, automation, and cloud-based data technologies. 
• Proactively learn and apply new frameworks and performance optimisation techniques. 

Requirements

• Bachelor's degree in computer science, Information Systems, or Data Science. 
• Certifications in Snowflake, Python, or data engineering technologies advantageous.

Experience

• 3–5 years of professional experience in data engineering. 
• Proven record of accomplishment of delivering and maintaining production-grade data pipelines. 
• Demonstrated ability to optimise data processes and integrate automation.