Senior Data Engineer - up to RM 10k
Summary
Senior Data Engineer in Kuala Lumpur (hybrid) at an FMCG organisation partnered via Randstad: designs and maintains scalable ETL/ELT pipelines, builds data models in Snowflake and Databricks, writes production Python, tunes performance, and collaborates with data scientists, analysts, and product managers.
- Hybrid Work Arrangement
- Career Growth
- Public Transport Accessible
about the company
Randstad has recently partnered with a renown organisation across Asia, within the FMCG industry. Your future employers operate and scale businesses across the continent, with a steady growth and utilization of digital solutions in streamlining the business operations.
key responsibilities:
Pipeline Architecture: Design, build, and maintain robust, highly scalable ETL/ELT data pipelines to ingest and process vast amounts of data from diverse sources.
Data Modeling & Warehousing: Architect and optimize data models within Snowflake and Databricks to ensure high performance and seamless data availability.
Development & Automation: Write clean, efficient, and well-documented Python code to process, transform, and integrate data while automating manual operational tasks.
Performance Tuning: Identify bottlenecks in existing infrastructure and implement structural improvements to enhance data delivery speed and system scalability.
Cross-Functional Collaboration: Partner closely with Data Scientists, Data Analysts, and Product Managers to understand specific data needs and deliver tailored infrastructure solutions.
requirements:
Experience: 3+ years of dedicated professional experience in Data Engineering.
Core Languages: Strong, production-level coding proficiency in Python.
ETL/ELT Development: Deep expertise in designing, deploying, and maintaining complex data pipelines from scratch.
Modern Data Stack: Hands-on, extensive experience working with Snowflake and Databricks in a production environment.
Database Knowledge: Advanced SQL knowledge and experience working with both relational databases and data lakes.
nice to haves:
Cloud Ecosystems: Hands-on experience with major cloud platforms and their native data services (AWS, Google Cloud Platform, or Microsoft Azure).
Orchestration & Streaming: Familiarity with data orchestration tools (e.g., Apache Airflow, dbt) and real-time streaming technologies (e.g., Kafka).
Infrastructure as Code: Experience with Terraform or similar IaC tools.
experience
4 years
skills
ETL, Python, Databricks, Snowflake
qualifications
no additional qualifications required
education
Vocational/Professional Qualification