Data Engineer Lead - Pasir Ris

You will take ownership of the entire data engineering function, combining proactive leadership, strong process thinking, and technical expertise to establish robust data pipelines, enforce governance, and collaborate cross-functionally. You will also build and mentor a growing data engineering team to support the company’s digital transformation.

Key Responsibilities:

1. Cloud Data Warehouse Architecture

• Spearhead the 0-to-1 design and implementation of a modern, cloud-native data warehouse (e.g., BigQuery, Snowflake, Redshift) that consolidates data from ERP, CRM, e-commerce, inventory systems, and existing MySQL databases.
• Lead the full architecture, infrastructure setup, and deployment, ensuring security, scalability, and performance optimization from day one.

1. Build & Scale the Data Engineering Team

• Establish the data engineering function from the ground up, defining standards for documentation, tooling, and agile workflows.
• Recruit, lead, and mentor a high-performing data engineering team, fostering a culture of excellence in data modeling, ETL automation, and system reliability.

1. ETL Pipeline Development

• Design and build fully automated, scalable ETL/ELT pipelines using tools like Apache Airflow, Talend, or equivalent, to transform raw data into structured, high-value datasets.
• Prioritize maintainability, availability, and data integrity, incorporating robust testing and monitoring frameworks.

1. AI & Machine Learning Enablement

• Collaborate closely with AI/ML teams to prepare model-ready datasets that accelerate model training, deployment, and performance evaluation.
• Develop and maintain frameworks for continuous pipeline enhancement, enabling advanced analytics like personalization, recommendation engines, and predictive insights.

1. Data Quality & Governance

• Implement automated data cleansing, validation, and monitoring systems to ensure consistently high data quality.
• Ensure compliance with PDPA, GDPR, and internal data governance policies, implementing fine-grained access controls, auditing, and logging.

1. Scalable Architecture & Performance Tuning

• Design systems to support both real-time and batch data processing at scale.
• Proactively monitor, profile, and optimize the performance of data pipelines and data warehouse storage/querying layers.

1. Cross-Functional Partnership

• Partner with BI, analytics, and business teams to translate strategic objectives into scalable data solutions.
• Support the development of data visualization dashboards and self-service analytics platforms, promoting data-driven decision-making across the organization.

Required Skillsets and Qualification:

• Bachelor’s degree in Computer Science, Data Engineering, or related field; Master’s degree is a plus.
• 5+ years of experience in data engineering, with hands-on experience building cloud data infrastructure and teams from scratch.
• Expertise in SQL, Python, and cloud data platforms (e.g., GCP, AWS, Azure).
• Deep knowledge of data warehousing technologies (BigQuery, Snowflake, Redshift) and ETL orchestration tools (e.g., Airflow, Talend).
• Strong understanding of data governance, compliance, and metadata management.
• Proactive mindset with strong ownership over deliverables and outcomes.
• Excellent process thinking, capable of standardizing workflows and improving data operations efficiency.
• Proven ability to lead and mentor team members and collaborate with cross-functional teams, especially data science and business intelligence units.

What We Offer:

• A collaborative and supportive work environment.
• Opportunities for professional growth and career development within Mister Mobile.