Software Backend Engineer

Location: Singapore, Singapore

Thales people architect solutions that are relied upon to deliver operational advantage at every decisive moment throughout the mission. Defence and armed forces customers rely on us to deliver the full range of defensive systems for land, sea, and air. From early warning, to threat neutralisation, our platforms cover all levels from very short-range systems, to extended protection across the entire battle-space including Airspace Mobility Solutions, Vehicles and Tactical Systems and Missile Defence, Optronics, and Radar.

Thales established its presence in Singapore in 1973 to support the expansion of aerospace-related activities in the Asia-Pacific region. Throughout the last four decades, the company grew from strength to strength and is today involved in the primary businesses of Aerospace (including Air Traffic Management), Defence & Security, Ground Transportation and Digital Identity & Security. Thales today employs over 2,100 people in Singapore across all its business areas.

**ROLE DESCRIPTION SUMMARY**

As a Backend Software Engineer at AIR Lab, you will thrive if you have a passion for coding, designing, and engaging in discussions about APIs and data processing, including areas like data modeling, stream processing, and data quality control. You take pride in both the quality of your technical implementations and the overall delivery. You enjoy collaborating with a diverse team, bringing together various ethnic and cultural perspectives.

**KEY ACTIVITIES AND RESPONSIBILITIES**

**As a** Software Backend Engineer**, you are accountable for**:

- Design and build APIs to provide data for the stream-aligned squads.
- Implement features and associated automated unit and integration tests. If appropriate implement security and load tests.
- Improve and maintain the DataLake cybersecurity posture w.r.t data governance and cybersecurity standards by working with other stakeholders (e.g., Data Architect, Data Assessment Office, Cybersecurity Office).
- Improve and maintain the DataLake service levels for reliable data flow, health of infrastructure (i.e., compute and storage) and security.
- Improve and maintain the total cost of ownership of data; this activity includes raising efficiencies around FinOps, CloudOps.
- Improve and maintain the architecture transforming data between the DataLake and a distributed search and analytics engine (e.g., ElasticSearch).
- Lead the technical evolution of the DataLake by exploring new methods, techniques, algorithms (e.g., data meshes, AI/MLOps infrastructure).
- Work with the Data Architect to effect best practices to the engineering organization.
- Write and review the necessary technical and functional documentation in documentation repositories (e.g., backstage.io, JIRA, READMEs).
- Work in an agile, cross-functional multinational team, actively supporting the team's success.

**KEY KNOWLEDGE AND EXPERIENCE**

**To be successful in your role, you will have demonstrated and/or acquired the following knowledge and experience**:
**Education**
- Bachelor's degree in Computer Science or Information Technology with a minimum of 3 years of working experience.
- Master's degree in Computer Science or Data Science, if applicable

**Essential Skills/Experience**
- Familiar with development and deployment technologies for cloud (e.g., Azure Cloud, AWS, GCP), Kubernetes and container workloads (e.g., Kaniko, Docker) in general.
- Proficient in designing and implementing data processing and business Logic
- Proficiency in distributed source code management tools like GitLab, Github and practice GitOps
- Effective communication skills in English

**Desirable Skills/Experience**
- Working knowledge of other languages (e.g., Python3, Scala2 or Scala3, Go, TypeScript, C, C++17, Java17)
- Experience in designing ETL or event-driven processing pipelines (with structured or unstructured data) using frameworks like Spark/ Apache Beam, Kafka Streams, Flink; proficient in deploying these data pipelines into Kubernetes cluster in Azure cloud either as virtual machines or containerized workloads.
- Familiar with cloud deployment models (e.g., public, private, community and hybrid) and service models (Software as a Service, Platform as a Service and Infrastructure as a Service).
- Familiar with designing and/or implementing AI/MLOps pipelines in public cloud (e.g., Azure, AWS, GCP)

**Essential / Desirable Traits**
- Possess learning agility, flexibility and pro-activity
- Comfortable with agile teamwork and user engagement

**YOUR CAREER AT THALES**

Future opportunities will allow you to discover other domains or sites. You will be able to evolve and grow your competencies in different areas:

- Room and attention to personal development
- Build your talents in another domain of Thales Group, discovering new products, new customers, new country or go to a more complex Solution.
- Choose between a technical expertise or a leadership path
- Build an in