Senior Data Engineer

3 days ago

Kuala Lumpur, Kuala Lumpur, Malaysia Usobi Full time


Nationality: Prefer Malaysian Chinese, but can share resume as well for Malaysian Indian, will let Hiring Manager review first
Location: Kuala Lumpur, Malaysia
Working Hours: 9:30 AM 6:30 PM (GMT +8)
Salary Range: USD 1,700 USD 3,200 / month (approx. RM8,000 RM15,000)Job Overview-
We are seeking a Senior Data Engineer to lead the design and implementation of a scalable data architecture to support our expanding application ecosystem. This is a high-impact role that involves selecting the right technologies, building robust pipelines, and ensuring our data platform is optimized for performance, security, and business intelligence.

You'll work closely with engineering, analytics, and business stakeholders to assess current data sources, propose a unified data strategy, and enable data-driven decision-making across the organization.

The essentials of the role:
Analyze the current ecosystem involving multiple source databases (SQL, NoSQL,
APIs, etc.) and identify integration points for a unified data platform.
Evaluate and compare potential data lake and data warehouse solutions (e.g.,
Hive, Delta Lake, BigQuery, Snowflake, Redshift) based on cost, performance,
scalability, and team needs.
Propose and implement the most appropriate architecture for both batch and
real-time data ingestion and processing.
Design and build efficient, secure, and reliable ETL/ELT pipelines for structured
and semi-structured data.
Ensure the resulting architecture supports data discoverability, query
performance, lineage tracking, and governance.
Collaborate with data analysts, product teams, and backend developers to
ensure seamless data access and usability.
Define and enforce standards around data quality, security, and compliance.
Stay up to date with industry best practices and emerging technologies in data
engineering and cloud infrastructure.
Requirements:
5+ years of professional experience in data engineering or backend data
intensive roles.
Proven experience in designing and implementing data pipelines, data lakes,
and data warehouses in cloud or hybrid environments.
Strong command of SQL, data modeling, and performance tuning.
Hands-on experience with data pipeline tools such as Apache Airflow, Spark, or
equivalents.
Familiarity with various data storage and processing systems including traditional
RDBMS, NoSQL, and streaming platforms (Kafka, Kinesis, etc.).
Experience in evaluating and selecting data storage and compute platforms (e.g.,
Hive, Redshift, Snowflake, Delta Lake).
Experience with cloud platforms such as AWS, GCP, or Azure.
Excellent communication and stakeholder management skills.
Experience with Hive, HDFS, or Hadoop ecosystem components.
Background in data governance, security frameworks, and compliance (GDPR,
HIPAA, etc.).
Proficiency in scripting or programming languages like Python, Scala, or Java.
Experience with real-time data processing architectures.

Employee Benefits (for confirmed staff only)-
Lunch Allowance: RM18 per working day (applicable for working in office)Transportation Allowance / Season Parking Card

Medical Claims (limits based on job level)Dental & Optical Claims (limits based on job level)Annual Leave: Starting from 14 days for Senior-level employees

Overtime Pay: Provided according to Malaysian labor law


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