全职 Data Engineer (Mid-Level-Senior) 工作, 薪水, Optimum Solutions Pte Ltd 公司招聘中 - Ricebowl

Responsibilities

Craft and Execution

• Design architectures for moderately complex data systems and platforms, with careful consideration for scalability, reliability, and long-term maintainability.
• Proactively address technical debt through refactoring to maintain system stability over the long term.
• Implement advanced DataOps practices, including automated pipeline deployment, workflow monitoring, and data observability.
• Apply advanced ETL/ELT methods to prepare and transform data for complex use cases.
• Use advanced data modelling approaches to accurately represent complex business processes.
• Apply advanced data integration methods, including data streaming, CDC, and message queues, when developing data pipelines and components.
• Effectively manage data privacy, governance, and regulatory requirements, ensuring system designs comply with relevant policies and standards.
• Develop comprehensive plans to achieve key milestones by clearly defining, breaking down, and prioritising tasks.
• Communicate and collaborate effectively with team members and stakeholders to ensure coordinated and aligned delivery.

Ownership

• Take end-to-end ownership of broad projects with ambiguous scope and drive them towards successful outcomes.
• Take considered risks and use both successes and failures as opportunities to learn and grow.
• Mentor and support junior team members through knowledge sharing, problem decomposition, and constructive feedback.
• Contribute actively to improving team productivity and capability through hands-on guidance and support.

Strategic Alignment

• Translate team objectives into actionable plans by breaking down work and prioritising tasks effectively.
• Proactively identify opportunities, lead workstreams, and synthesise data into clear recommendations linked to organisational impact.
• Identify and mitigate project-level risks by anticipating potential challenges before they arise.

Culture and Organisational Influence

• Coordinate cross-functional collaboration and provide guidance to team members to support effective project delivery.
• Navigate and help resolve disagreements constructively, facilitating alignment across team members and stakeholders.
• Constructively challenge existing processes to support continuous improvement and drive change initiatives at both team and division levels.
• Actively share learnings from both successes and failures, providing recommendations that improve team performance and strengthen a culture of continuous learning.

What we are looking for

Experience and Education

• Bachelor's degree or higher in Data Science, Computer Science, Statistics, Applied Mathematics, or another related quantitative field.
• A minimum of 5 years of data engineering experience.
• Demonstrated experience delivering data platforms or products within large-scale enterprise environments.

Required Skills

• Strong expertise in data modelling, including OLTP, OLAP, and dimensional modelling approaches.
• Experience working with cloud data platforms and technologies such as AWS, Azure Synapse/Microsoft Fabric, Snowflake, Databricks, Redshift, and Data Lakes.
• Proficiency in big data technologies, including Hadoop, Spark, Kafka, and Flink.
• Strong programming capabilities in Python, Scala, or Java.
• Experience with CI/CD and DataOps practices, including SHIP-HATS or equivalent frameworks.
• Strong expertise in data integration approaches, including ETL/ELT, streaming, and APIs.

Preferred Skills

• Understanding of machine learning and LLM concepts, including prompt engineering and AI application development.
• Familiarity with MLOps practices and the deployment of machine learning solutions in cloud environments.
• Awareness of responsible AI principles, including fairness, robustness, and safety.