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As a Data Engineer, you will play a crucial role in designing, developing, and maintaining the data infrastructure that powers our organization's data-driven initiatives. You will work closely with cross-functional teams, including data scientists, analysts, and business stakeholders, to understand requirements and ensure the availability, reliability, and efficiency of our data pipelines and systems. This role is split approximately 70% data engineering and 30% AI/agentic development, and is well suited to someone who wants to grow at the intersection of data infrastructure and applied AI.
Key responsibilities
- Design, develop, and maintain robust, scalable, and efficient data pipelines to ingest, transform, and store data from various sources into our data lake/data warehouse.
- Develop and maintain Airflow DAGs to orchestrate, schedule, and monitor existing and new data pipelines, improving visibility into pipeline health and failure recovery.
- Collaborate with data analysts to understand their data requirements and implement data transformations and aggregations to support their analyses and reporting needs.
- Perform research on various data sources and evaluate the value and applicability to property development, including residential property and retail mall.
- Develop scripts that perform web-scraping to acquire data that are openly available online.
- Build and manage CI/CD pipelines to automate the deployment and testing of data pipelines and infrastructure.
- Utilize Azure cloud services, AWS cloud services, and other relevant technologies to architect, implement, and manage data solutions.
- Monitor, troubleshoot, and optimize data pipelines for performance, reliability, and scalability.
- Design and build AI agent solutions using CrewAI or the LangChain ecosystem, including tool integration and multi-agent workflows.
- Build and maintain RAG pipelines (ingestion, embedding, retrieval) to ground LLM outputs in company data.
Requirements
- Bachelor's or Master's degree in Data Science, Computer Science, Engineering, or a related field.
- Proven experience as a Data Engineer or in a similar role, with a strong understanding of data engineering concepts, techniques, and best practices.
- Hands-on experience with cloud solutions, particularly in designing, building, and optimizing data pipelines using Azure cloud services (Azure Function, Azure Data Factory, Azure Databricks, etc.) and/or AWS cloud services (AWS Glue, Lambda, Amazon Redshift, etc.).
- Proficiency in programming languages such as Python, Java, or Scala, and experience with data processing frameworks (e.g., Spark, Hadoop) and ETL / ELT tools.
- Experience with Apache Airflow (or similar workflow orchestrators such as Dagster/Prefect) for orchestrating, scheduling, and monitoring data pipelines.
- Strong knowledge of data modelling, data warehousing, and database technologies.
- Working knowledge of Agentic AI concepts, i.e. LLMs, RAG, agent tools/function-calling, and multi-agent orchestration, with hands-on exposure to frameworks such as LangChain, LangGraph, or CrewAI.
- Excellent problem-solving skills and the ability to troubleshoot complex data-related issues.
- Strong communication and collaboration skills to work effectively with cross-functional teams.
- Ability to adapt to a fast-paced and evolving environment while delivering high-quality solutions.
About us
ASIAN PAC Group of companies operates in the Business Analytics and Strategy division.