Platform and Data Engineer at Ensign Services, Inc.

Singapore, Singapore, Singapore -

Full Time

Start Date

Immediate

Expiry Date

24 Dec, 25

Salary

0.0

Posted On

25 Sep, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Engineering, Python, Spark, Go, Bash, Git, GitLab, Docker, Kubernetes, AWS, Linux, Automation, DevSecOps, Agile, CI/CD, Hadoop

Industry

Hospitals and Health Care

Description

Ensign is hiring ! Reporting to Head, Platforms and Data Engineering, the Platforms and Data Engineer will work closely with Data Scientists, Threat/Malware Researchers, Project Managers and Infrastructure Engineers to develop and manage high-performance analytics solutions. The incumbent will be accountable for the design, development, deployment and maintenance of AI analytics platforms as well as its data processing workflows. Key Responsibilities: Familiarize with Ensign’s business domain and objectives to develop and deploy data solutions that meet internal business requirements and the needs of partners and customers Design, develop, test, deploy operational data transformation processes. Design, develop, manage data lake, data warehouse architecture and relational databases. Provide monitoring, maintenance and support for data operations as part of maintenance & support as required in client projects. Embrace the challenge of dealing with terabytes of data on a daily basis. Manage development, staging, production environments to provide overall system functionality, health, scalability, resiliency, and security. Responsible for implementing and maintaining complex AI analytics projects, focus on large sets of data to turn information into insights using multiple platforms. Deliver detailed documentation and ensure quality throughout project lifecycle. Qualifications/Requirements: Bachelor’s degree in Computer Science /Computer Engineering or equivalent Experience in programming (Spark, Python, Go, Bash) for data engineering purposes Understanding of modern software engineering tools such as Git, GitLab Familiarity with Docker, Kubernetes and cloud services (AWS) Familiarity with network concepts. Comfort and experience working in Linux environment Aptitude for automation and software profiling Proven ability to handle multiple customer projects concurrently Detail-oriented, solution-focused and problem solver Preferred Skills (Good to haves): Minimum 3 years of experience developing data engineering pipelines Knowledge of different data platforms (e.g. Kafka, MongoDB, Postgres, Elasticsearch), associated tools and cloud-based technologies (e.g. Lambda, Glue). Have strong knowledge in DevSecOps to design, develop, test, and deploy applications for customer projects. Experience in Cyber Security / Telco industry will be an advantage Knowledge in Agile and CI/CD is desirable Familiarity with virtualization platform (Proxmox, VMware, KVM) Familiarity with Hadoop ecosystem and MPP databases Ability to demonstrate programming skills and knowledge without being overly dependent on AI. *Singaporeans only as the candidate may potentially be subjected to clearance depending on projects About Ensign InfoSecurity Ensign InfoSecurity is the largest pure-play cybersecurity service provider in Asia. The company is headquartered in Singapore. We specialise in the provision of these services; cybersecurity advisory and assurance, implementation and management of advanced cybersecurity controls, cybersecurity monitoring, threat hunting, and incident response. Underpinning these competencies is in-house research and development in cybersecurity. What Makes Ensign Special? We are a technology company with warmth and soul. We are ambitious, propelled by our vision to be the cyber defender of choice, and fueled by the dedication and camaraderie of individuals who are eager to make a difference, and leave their footprints in the industry. If you are a self-motivated curious go-getter, we want You! Join Us!

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Responsibilities

The Platforms and Data Engineer will develop and manage high-performance analytics solutions, working closely with various teams. Responsibilities include designing, developing, deploying, and maintaining AI analytics platforms and data processing workflows.