Data Engineer (6m contract)

Job Description

The Customer Lifecycle Management (CLM) team at StarHub is dedicated to understanding, enhancing, and optimizing the customer journey. From acquisition to retention, the CLM team employs data-driven strategies to provide unparalleled customer experiences. Through a combination of data science, business intelligence, customer insights, NPS, and digital analytics, the CLM team ensures that StarHub's offerings are aligned with customer needs, leading to increased loyalty, satisfaction, and growth.

The Data Engineer will join the CLM team on a 6-month contract to lead the migration of legacy data infrastructure from Neteza (IBM PureData) to Snowflake. This role is critical for modernizing StarHub's data platform, ensuring seamless transfer of existing tables, data pipelines, and ETL processes to the cloud-native Snowflake environment. The Data Engineer will work closely with Data Science, Business Analytics, and Digital Analytics teams to ensure migrated data maintains integrity, accessibility, and performance standards required for ongoing customer analytics and business intelligence initiatives.

KEY RESPONSIBILITIES

• Legacy Data Migration: Migrate existing tables, schemas, and data assets from Neteza to Snowflake, ensuring data integrity and completeness throughout the migration process.
• ETL Pipeline Conversion: Convert and optimize existing ETL/ELT processes to work with Snowflake, leveraging cloud-native features for improved performance and scalability.
• Schema Design & Optimization: Redesign and optimize data models, dimensional schemas, and data marts for the Snowflake environment while maintaining compatibility with downstream analytics.
• Data Validation & Testing: Develop and execute comprehensive data validation frameworks to verify accuracy and consistency between source (Neteza) and target (Snowflake) systems.
• Migration Documentation: Create detailed migration runbooks, data dictionaries, and technical documentation to support knowledge transfer and operational continuity.
• Stakeholder Collaboration: Partner with Data Science, Business Analytics, and Digital Analytics teams to prioritize migration activities and minimize disruption to ongoing analytics operations.

Qualifications

Education Level:

• Bachelor's degree in Computer Science, Information Systems, Data Engineering, or a related field. Master's degree in a relevant field is preferred.

Required Experience and Knowledge:

• 3-5 years of experience in data engineering or a related field
• Strong knowledge of data warehouse concepts, ETL processes, and data modeling techniques
• Experience with data migration projects, particularly from legacy on-premise systems to cloud platforms
• Hands-on experience with Neteza (IBM PureData) or similar legacy data warehouse systems (e.g., Teradata, Oracle)
• Experience with cloud-based data platforms, specifically Snowflake and AWS
• Proficiency in SQL and experience with NoSQL databases
• Knowledge of data governance principles and data privacy regulations

Job-Specific Technical Skills:

• Proficiency in Python or Scala for data processing and automation
• Experience with ETL tools (e.g., Apache NiFi, Talend, Informatica)
• Experience with Snowflake-specific features (Snowpipe, Tasks, Streams, Time Travel, Zero-Copy Cloning)
• Familiarity with data migration tools and methodologies
• Knowledge of data visualization tools (e.g., Tableau, PowerBI) to support data quality checks and pipeline monitoring
• Familiarity with version control systems (e.g., Git) and CI/CD practices
• Experience with container technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes)
• Understanding of data security best practices and implementation

Behavioural Skills:

• Strong problem-solving and analytical skills
• Excellent communication abilities to collaborate with technical and non-technical team members
• Proactive approach to identifying and resolving data-related issues
• Ability to manage multiple projects and priorities effectively
• Detail-oriented with a focus on data quality and system reliability
• Adaptability to work with evolving technologies and changing business requirements
• Strong teamwork skills and ability to work in a collaborative environment