Data Engineering Manager

Kuala Lumpur, Malaysia

Job Description

About the Role
As a Data Engineer Manager, you will be part of a dynamic team where you will be working closely with other Tech Leads to drive & lead the design and implementation of DMP of Data Hub & Lake. You will be driving the technical implementation roadmap with the Cluster Tech Lead. Furthermore, you will be involved in developing data flows interacting with various systems using various protocols as well as Data computation, aggregation, transformation will be part the core delivery. As we are building a data management platform as part of Swift's strategy to enable frictionless transaction, you together with our dynamic team of professionals using up-to-date technologies will be delivering data management features and capabilities managing & delivering data across different business practices internally and externally. You will develop the platform that is based on industries best practices, standards and governance framework that are robust, scalable & performant as well as ensuring high data quality and data integrity.

What to expect:

  • Proven strong experience in Data Engineering and Software Development Practices
  • Hands-on experience with Big data stack: Apache Spark and S3 is a strong advantage
  • Experience with RDBMS (Oracle/Postgresql) or NoSQL
  • Hands-on experience with Apache NiFi, Hadoop, Hive and Air Flow is a plus
  • Experience in software architecture design as key technical resource leading the development of solutions
  • Strong understanding advanced security concepts and implementation
  • Strong understanding of Identity & Access management, Authentication & Authorization: LDAP, Active Directory, Radius, federation, SAML
  • Strong understanding in networking concepts: TCP/IP, VPN, reverse proxies, firewalls
  • Experience with CICD development & deployment tools such as Maven, Jenkins, Nexus and Git
  • Experience with programming language, primarily Python, Java, Unix Shell
  • Experience with Virtualization concepts and orchestration technologies such as Docker, Open-Shift, Kubernetes
  • Demonstrated ability to influence and consult (providing options with pros, cons and risks) around all key technical decisions during project delivery
  • Knows or wants to learn how to translate business problems into software & technical requirements
  • Good interpersonal skills, customer centric attitude, ability to deal with cultural diversity
  • Practical working experience in an Agile development (scrum) context
What will make you successful?
  • At least 10+ years' of relevant experience and at least last 5 years working as a Technical Lead
  • University degree in computer science or related Engineering discipline
  • Strong communication skills in English (both written and verbal)
  • Team player, experience working in a multicultural environment
  • Able to lead, coach and groom junior team members
  • Able to learn new technologies quickly
  • Able to thrive in a fast paced, goals and deadlines driven environment
To know the team better, you may review some of the team members LinkedIn profile:
  • Elizalde Esteban - Chapter Lead - DevOps Engineering (Hiring Manager)
  • Hai Dong Nguyen - Chapter Lead/Tech Lead
What we offer

We put you in control of career
We give you a competitive package
We help you perform at your best
We help you make a difference
We give you the freedom to be yourself

We give you the freedom to be yourself. We are creating an environment of unique individuals - like you - with different perspectives on the financial industry and the world. An environment in which everyone's voice counts and where you can reach your full potential regardless of age, background, culture, colour, disability, gender, nationality, race, religion , or veteran/military status.

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Job Detail

  • Job Id
    JD855528
  • Industry
    Not mentioned
  • Total Positions
    1
  • Job Type:
    Full Time
  • Salary:
    Not mentioned
  • Employment Status
    Permanent
  • Job Location
    Kuala Lumpur, Malaysia
  • Education
    Not mentioned