Data Engineer

2 days ago

Greater Kuala Lumpur, Malaysia Second Talent Full time 60,000 - 120,000 per year

About the Role

We are looking for a
Data Engineer
to design, build, and maintain scalable data pipelines and platforms that power advanced analytics and AI solutions. You will work with modern
Google Cloud data technologies
to enable high-quality, reliable, and timely data for the business, with a focus on building new capabilities and ensuring platform reliability.

Look for candidates with solid
end-to-end data engineering experience
— those who have built or designed data pipelines, data models, and ETL/ELT workflows rather than just supporting existing ones. Ideal profiles show exposure to
enterprise-scale data modernization or migration projects
, working across multiple data sources and collaborating with data or BI teams.

For
GCP
, target skills like
BigQuery, Dataflow, Cloud Composer (Airflow), DataProc (Spark), Cloud Run, Pub/Sub, and GCS
, plus certifications such as
GCP Professional Data Engineer
or
Cloud Architect
.

For
Azure
, focus on
Data Factory, Databricks (PySpark), Synapse Analytics
, and
Azure Data Lake
, as these are highly transferable.

Strong supporting skills include
SQL optimization, Airflow/dbt orchestration, CI/CD pipelines
, and
CDC or data governance
exposure — all indicators of someone ready to perform in a
GCP-based retail data platform project
.

Key Responsibilities

  • Pipeline Development:
    Design, build, and maintain batch and streaming data pipelines using GCP services such as BigQuery, Dataflow, Dataproc, Composer, Dataform, and Cloud Functions.
  • Data Modeling & Optimization:
    Implement and optimize data models in BigQuery to support analytics, BI reporting, and machine learning workloads.
  • Data Integration:
    Connect and transform data from multiple sources, including APIs, databases, event streams, and flat files.
  • Platform Reliability:
    Monitor and troubleshoot data pipelines, ensuring high availability, scalability, and cost efficiency.
  • Governance & Quality:
    Implement data validation, quality checks, and security best practices to ensure trusted data.
  • Collaboration:
    Work closely with analysts, BI developers (Tableau, MicroStrategy), and business teams to enable reporting and self-service analytics.
  • Legacy Support (Light):
    Provide occasional support for legacy systems (Oracle, MicroStrategy) where needed, focusing on data extraction and gradual modernization.

Requirements

  • Experience:
    3–5 years of hands-on experience in data engineering, ETL/ELT development, or related roles.

Technical Skills

  • Strong SQL and Python skills for data transformation and automation.
  • Hands-on experience with GCP Data Stack (BigQuery, Dataflow, Composer, Dataproc, Dataform).
  • Familiarity with orchestration workflows (Airflow/Composer) and CI/CD for data pipelines.
  • Data Modeling:
    Understanding of relational, dimensional, and modern data modeling concepts, with an eye for performance optimization.
  • Cloud Knowledge:
    Exposure to Azure Data Stack (Synapse, Data Factory, Databricks) is a plus.
  • Mindset:
    Proactive, detail-oriented, and eager to work on building modern, scalable data solutions.

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