Senior Data Engineer

RHB Bank; Kuala Lumpur; On-site; MYR 80,000 - 100,000; Full time

Job summary

A leading financial institution in Kuala Lumpur is seeking an experienced Data Engineer to design and optimize data pipelines across various platforms. This role requires hands-on experience with Python, SQL, and Spark, along with skills in ETL/ELT tools and streaming technologies. Candidates must exhibit strong leadership and mentoring abilities, supporting junior engineers in their growth while ensuring data quality and performance tuning. The job emphasizes collaboration with business teams and stakeholders.

Qualifications

• 5–8+ years of hands-on experience in Data Engineering.
• Strong expertise in Python, SQL, Spark, and PySpark.
• Experience with performance tuning for ETL flows.

Responsibilities

• Design and optimize end-to-end data pipelines across platforms.
• Implement ETL/ELT processes and ensure data quality.
• Provide mentorship to junior engineers and guide their growth.

Skills

Python

SQL

Spark

ETL/ELT tools

Kafka

Data modeling

DevOps

Tools

NiFi

Airflow

Hadoop ecosystem

Postgres

Job description

• Design, build, and optimize end-to-end data pipelines (batch & streaming) across Enterprise Data Lake, DWH, and analytics platforms.
• Implement efficient ETL/ELT processes using tools such as Spark, Python, SQL, Kafka, NiFi, or Airflow.
• Work with both structured and semi/unstructured data and ensure high performance, scalability, and data quality.
• Lead root-cause analysis and optimize data pipeline performance across systems (Hive, Impala, Iceberg, Oracle & Postgres).
• Provide guided mentorship to junior and mid-level engineers—pair programming, code reviews, and hands-on coaching.
• Train the team on best engineering practices, including coding standards, documentation, version control, testing, and pipeline monitoring.
• Conduct knowledge-sharing sessions (SQL tuning, data modeling, Spark optimization, Git, CI/CD, coding patterns, etc.).
• Guide juniors in problem-solving, prioritization, and understanding enterprise data concepts.
• Act as a technical escalation point for complex pipeline issues.
• Help team members create learning roadmaps and support their growth in modern data engineering.

3. Collaboration & Stakeholder Management

• Work closely with business teams, data analysts, data scientists, and platform teams.
• Translate business requirements into scalable engineering solutions.
• Communicate clearly with both technical and non-technical stakeholders.

Required Skills & Qualifications

• 5–8+ years of hands-on experience in Data Engineering.
• Strong expertise in:
  • Python, SQL, Spark, PySpark
  • ETL/ELT tools (NiFi,Airflow)
  • Streaming technologies (Kafka, Spark Streaming)
  • Hadoop ecosystem (Hive, Impala, Iceberg preferred)
  • RDBMS & Data Warehouse
• Solid understanding of:
  • Data modeling (3NF, Star Schema, Lakehouse layers)
  • Data governance, quality frameworks, lineage tools
  • DevOps & CI/CD (Git, Jenkins, Docker)
• Experience with performance tuning (Spark jobs, SQL queries, ETL flows).

Soft Skills

• Strong leadership, communication, and collaboration abilities.
• Passionate about mentoring and developing others.
• Able to simplify complex technical concepts for junior team members.
• Proactive, independent, and solution-oriented mindset.