Data Engineer (Risk Control)

Hytech Consulting Management; Kuala Lumpur; On-site; MYR 70,000 - 90,000; Full time

Job summary

A leading data consulting firm is seeking a Data Engineer skilled in cloud-based data platforms to design scalable data pipelines. Responsibilities include developing ETL processes, collaborating with teams to model data, and ensuring data quality. The ideal candidate has 3-5 years' experience in data engineering, strong SQL skills, and cloud platform knowledge. Competitive package offered in a fast-paced environment.

Benefits

Competitive compensation package

Cross-functional collaboration opportunities

Dynamic industry environment

Qualifications

• 3–5 years of experience in data engineering or backend engineering.
• Hands-on experience in large-scale data processing.
• Strong proficiency in SQL and experience with Python or Scala.

Responsibilities

• Design, develop, and maintain ETL/ELT data pipelines.
• Collaborate with various teams for data modeling.
• Implement and maintain data quality monitoring.

Skills

Data processing

SQL

Python

Scala

Cloud computing

Data modeling

ETL/ELT orchestration

Data governance

Collaboration

Education

Bachelor’s degree in Computer Science or related fields

Tools

AWS

GCP

Azure

Spark

Flink

Kafka

Airflow

dbt

Dagster

Job description

We are seeking a highly skilled Data Engineer with experience in cloud-based data platforms to build scalable, reliable data pipelines and robust data models. This role will work closely with data teams, AI teams, and business stakeholders to ensure a solid data foundation that supports analytics, reporting, machine learning, and downstream data products.

Job Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines, including ingestion, cleaning, transformation, and loading into data lakes and data warehouses.
• Collaborate with Data Science, BI, Product, and Backend teams to translate business and analytical needs into reliable data models and table structures.
• Build and optimize Bronze, Silver, and Gold layers to ensure data consistency, performance, and usability.
• Manage batch and streaming data processing frameworks such as Spark, Flink, or Kafka, ensuring system stability and efficiency.
• Implement and maintain data quality monitoring, including schema validation, row-count checks, anomaly detection, and pipeline automation.
• Provide foundational datasets and feature pipelines to support AI and analytics teams.
• Work with platform and infrastructure teams to ensure availability, security, and scalability of the data platform.
• Contribute to data governance practices, including metadata management, data cataloging, field definitions, and versioning standards.
• Continuously improve pipeline performance, reduce processing costs, and enhance maintainability.

Qualifications

• 3–5 years of experience in data engineering or backend engineering, with hands‑on experience in large‑scale data processing.
• Bachelor’s degree or above in Computer Science, Information Systems, Data Engineering, or related fields.
• Strong proficiency in SQL and experience with Python or Scala for data processing.
• Experience with at least one major cloud provider (AWS / GCP / Azure); familiarity with S3, Glue, Lambda, Databricks, or similar platforms.
• Knowledge of distributed data processing technologies such as Spark, Flink, or Kafka.
• Solid understanding of data warehousing concepts and data modeling (Star Schema, Data Vault, Medallion Architecture).
• Experience with ETL/ELT pipeline orchestration tools such as Airflow, dbt, or Dagster.
• Strong communication skills and ability to collaborate with cross‑functional stakeholders.
• Detail‑oriented, proactive, and strong problem‑solving mindset.
• Experience in financial technology platforms, or risk‑related data is a strong advantage.

What we offer

• Clear role definition with well‑defined objectives
• Extensive cross‑functional and cross‑regional collaboration opportunities
• Diverse data scenarios with challenging product strategy initiatives
• Fast‑paced and dynamic industry environment
• Strong sense of ownership
• Competitive compensation package within a performance‑driven culture