Data Engineer

The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.

Data Engineer

Company Overview
This company is a leading provider of communications, entertainment, and digital services, with a strong focus on homegrown innovation. They offer a wide range of services across fibre and wireless infrastructure, working with global partners to bring mobile and fixed services, premium content, and a diverse array of communication solutions to both individuals and businesses. The company specializes in AI, cybersecurity, data analytics, IoT, and robotics to support corporate and government clients.

Role Overview
As a Data Engineer in the Customer Lifecycle Management (CLM) team, you will be responsible for designing, implementing, and maintaining the data infrastructure that supports analytics and data science initiatives. The role includes optimizing data pipelines, ensuring data quality, and collaborating with data scientists and analysts to enable data-driven decision-making that enhances customer experiences and drives business growth.

Key Responsibilities

• Data Pipeline Development: Design, implement, and maintain ETL (Extract, Transform, Load) processes to integrate data from various sources. Optimize existing pipelines for performance and scalability.
• Data Warehouse Management: Develop and maintain data warehouse architecture to meet team needs. Implement data modeling techniques to optimize storage and retrieval.
• Data Quality Assurance: Implement data quality checks and monitoring systems to ensure accurate data for analytics and reporting. Maintain data documentation and metadata.
• Big Data Technologies: Use technologies like Hadoop, Spark, and Kafka to efficiently process and analyze large volumes of customer data.
• Data Governance: Collaborate to implement data governance policies and ensure compliance with privacy regulations and internal standards.
• Infrastructure Optimization: Continuously improve data infrastructure to optimize performance, reduce costs, and enhance scalability. Automate data processes where possible.

Qualifications

• Education: Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or related field (Master’s preferred).
• Experience: 3-5 years in data engineering or a related field.
• Technical Skills:
  • Strong knowledge of data warehouse concepts, ETL processes, and data modeling techniques.
  • Experience with cloud-based platforms (e.g., AWS, Snowflake) and big data technologies (Hadoop, Spark, Kafka).
  • Proficiency in SQL and experience with NoSQL databases.
  • Experience with ETL tools (e.g., Apache NiFi, Talend, Informatica).
  • Familiarity with data visualization tools (Tableau, PowerBI).
  • Proficiency in Python or Scala for data processing and automation.
  • Experience with version control systems (e.g., Git) and CI/CD practices.
  • Knowledge of data security best practices and implementation.
• Behavioural Skills:
  • Strong problem-solving and analytical abilities.
  • Excellent communication skills for working with both technical and non-technical teams.
  • Proactive and detail-oriented, with a focus on data quality and system reliability.
  • Adaptability to evolving technologies and business requirements.

Disclaimer:
SpringCube curates tech job listings from various company websites to support tech professionals in Singapore during these challenging times.

1. No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
2. No Client Relationship: This company is not a client of SpringCube unless stated.
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4. No Liability: SpringCube is not liable for inaccuracies.