Job Description

Job Title:

Kafka Data Engineer - Digital Banking

Job Purpose

Design, develop, and maintain

Kafka-based data pipelines

and related technologies to deliver scalable, efficient, and comprehensive digital solutions that meet business needs.

Key Responsibilities

Design, develop, and manage

Kafka-based data pipelines

ensuring scalability, adaptability, and efficiency. Build expertise in

data migration

and

Change Data Capture (CDC)

with

Kafka Connect and Debezium

. Apply

event-driven architecture patterns

and Kafka best practices; guide development teams in adopting them. Assist developers with event modeling, ensuring data quality and integrity. Act as a

subject matter expert (SME)

for Kafka/Confluent through continuous learning. Work with

Kafka and Confluent APIs

(metadata, metrics, admin) to enable proactive insights and automation. Prepare and maintain documentation (data mapping, data dictionary). Design monitoring solutions and statistical reporting to support implementations. Provide

Level 2 & 3 BAU support

and optimize existing Kafka environments.

Requirements

Bachelor's degree in Computer Science, related field, or equivalent work experience.

3+ years' data engineering experience

, including

Kafka (on-premise)

. Strong knowledge of

Kafka, SQL (with tuning), and database fundamentals

. Solid understanding of

distributed systems

. Strong communication and interpersonal skills.

Good to Have

Experience with

Data Warehousing

and

Big Data technologies

. Knowledge of

Operational Data Store (ODS)

and

Change Data Capture (CDC)

. Expertise in

Debezium

. Relevant certifications in data engineering/programming.
Job Type: Full-time

Pay: RM11,000.00 - RM12,000.00 per month

Education:

Bachelor's (Preferred)
Experience:

Banking domain knowledge: 1 year (Preferred) MSSQL: 3 years (Preferred) SQL scripting, Stored Procedure: 2 years (Preferred) performance tuning (query/database/etl): 2 years (Preferred) data engineering , including Kafka (on-premise).: 2 years (Required) Kafka connectors: 2 years (Preferred) messaging and stream processing on Kafka: 2 years (Preferred) KSQL: 2 years (Preferred) Python: 2 years (Preferred)
Work Location: In person