Data Engineer
Posted Updated
Employer Highlight:
- A Malaysian ICT professional services and systems integration company established on 22 March 1999.
- 25+ years of experience delivering enterprise ICT and systems integration solutions across Malaysia.
- Exposure to enterprise-scale digital transformation projects, including cloud, cybersecurity, networking, infrastructure, and managed services.
Project/Goal:
- Working in client's office, serving current project in the healthcare industry
Key Responsibilities:
- Design and implement scalable data lakehouse architectures using modern technologies.
- Build and maintain ETL/ELT pipelines for batch and real-time data processing
- Develop data ingestion frameworks from various sources (APIs, databases, files, streams)
- Optimize data storage, partitioning, and query performance in lakehouse environments
- Support machine learning workflows and AI model deployment pipelines
- Design disaster recovery and backup strategies for critical data assets
Skills Requirements:
- Programming: Python, Scala, Java, SQL, Shell scripting
- Big Data: Apache Spark, Hadoop ecosystem, Delta Lake, Apache Iceberg
- Cloud Platforms: AWS (S3, EMR, Glue, Lambda), Azure (ADF, Synapse), GCP (Dataflow, BigQuery)
- Data Platforms: Databricks, Snowflake, Apache Airflow, dbt
- Streaming: Apache Kafka, AWS Kinesis, Azure Event Hubs
- Infrastructure: Terraform, Docker, Kubernetes, Git
- Databases: PostgreSQL, MongoDB, Cassandra, Redis
Good to Have:
- Experience with real-time streaming platforms (Kafka, Kinesis, Pub/Sub)
- Experience with MLOps and ML pipeline orchestration
- Understanding of data privacy regulations (GDPR, Malaysian PDPA)
- Previous experience in financial services, e-commerce, or technology sectors
Work Location:
- Petaling Jaya, onsite
Career Level:
- Mid to Senior level with 4-6 years of experience.
Skills
- AI
- Airflow
- API
- AWS
- Azure
- Bash
- BigQuery
- Cassandra
- Cloud
- Cybersecurity
- Data Ingestion
- Databricks
- dbt
- Delta Lake
- Docker
- E-commerce
- ELT
- ETL
- GCP
- Gdpr
- Git
- Hadoop
- Iceberg
- Java
- Kafka
- Kinesis
- Kubernetes
- Lakehouse
- Lambda
- Machine Learning
- MLOps
- Model Deployment
- MongoDB
- Networking
- PostgreSQL
- Python
- Redis
- S3
- Scala
- Snowflake
- Spark
- SQL
- Terraform