Job title: Data Engineer Manager (Up to 240K)
Job type: Permanent
Emp type: Full-time
Industry: Banking & Financial Services
Functional Expertise: Information Technology (IT)
Salary type: Monthly
Salary: Negotiable
Location: Bangkok, TH
Job published: 2024-09-05
Job ID: 122263
Contact name: Pimchanok Yisarnkun

Job Description

More than just a recruitment company. At PRTR, we have been a part of our customer's success for 30 years as their total HR solutions partner. With 550 dedicated professionals and over 15,000 outsourced staff, we will continue to carry out our mission to develop a better career, a better life, and a better society, and thrive to become the No.1 people solutions organization in Southeast Asia.

Role Overview

As a Data Engineer Manager, you will lead a team of data engineers, analysts, and data scientists, driving the architecture, design, and implementation of scalable data solutions across the organization. You will manage the end-to-end data processes from data migration, warehousing, and lake architecture, ensuring the team delivers on key data-driven projects efficiently and accurately.

Key Responsibilities

  • Leading the data engineering team to design and implement scalable data architectures for both on-prem and cloud environments.
  • Developing and maintaining end-to-end data pipelines, ensuring efficient data ingestion, processing, and delivery for large-scale applications.
  • Collaborating with cross-functional teams, including IT, business development, and data science, to deliver integrated data solutions that align with business goals.
  • Ensuring compliance with data governance, quality standards, and security policies across all data projects.
  • Mentoring and developing team members, while driving the adoption of best practices in data engineering and pipeline development.

Qualifications

  • 7+ years of experience in data engineering, including managing experience.
  • Proven expertise in designing and implementing enterprise-scale data architectures across on-premises and cloud platforms (AWS, Azure, GCP).
  • Full-stack experience with data pipelines, ETL processes, and deploying machine learning products.
  • Strong knowledge of data governance, security protocols, and compliance requirements in large-scale enterprise settings.