Thales is a global technology leader trusted by governments, institutions, and enterprises to tackle their most demanding challenges. From quantum applications and artificial intelligence to cybersecurity and 6G innovation, our solutions empower critical decisions rooted in human intelligence. Operating at the forefront of aerospace and space, cybersecurity and digital identity, we’re driven by a mission to build a future we can all trust.
In Singapore, Thales has been a trusted partner since 1973, originally focused on aerospace activities in the Asia-Pacific region. With 2,000 employees across three local sites, we deliver cutting-edge solutions across aerospace (including air traffic management), defence and security, and digital identity and cybersecurity sectors. Together, we’re shaping the future by enabling customers to make pivotal decisions that safeguard communities and power progress.Whom We Are Looking For
We're on the lookout for Data Engineers eager to design, build, and optimize data pipelines and processing frameworks powering our next-generation Data Warehouse and Data Lakehouse solutions. If you're energized by discussing topics like streaming & batch processing, data quality, real-time data integration, advanced synchronization patterns, and modern architectural challenges such as stream-to-stream joins and backfilling—you’ll love this role.
You’ll thrive here if you:
- Are dedicated to building high-quality, production-ready data solutions, and champion excellence in technical delivery
- Enjoy collaborating in a diverse and inclusive team, exchanging ideas and learning across cultures
- Dive deep into data-centric problems, uncover elegant solutions, and are eager to share your knowledge to uplift your teammates
- Have a growth mindset, continuously explore new tools and technologies, and inspire those around you to innovate
Responsibilities:
- Integrate data from a variety of structured and unstructured sources (e.g., APIs, streaming platforms, databases, external data feeds)
- Architect, implement and maintain robust, scalable and efficient ETL/ELT pipelines to collect, ingest, transform and load data from diverse sources. Ensure these pipelines shall meet the performance requirements.
- Ensure all data pipelines, data transformations and data retrieval are compliant to the cybersecurity and regulatory requirements.
- Develop and optimize data models (relational and non-relational) to support analytics, and operational supporting needs.
- Develop data generation/tracing capabilities via data models, audit change model and visualization into dashboards.
- Participate in designing and evolving Data Warehouse architecture.
- Implement data validation, sanitization and monitoring processes to ensure integrity, accuracy and consistency of data, pro-actively identify data quality issues and develop solutions.
- Facilitate data synchronization between storage and processing systems
- Automate recurring data engineering tasks to improve efficiency and reliability
- Apply data lifecycle policies, authorization, access controls and encryption enablement.
Requirements:
Education
- Bachelors in Computer Science or Information Technology
- Masters degree in Computer Science or Data Science, if applicable
Essential Skills/Experience
- Proficient in data processing algorithm selection that respects balancing latency, throughput (e.g., Spark Structured Stream versus Flink DataStream).
- Proficiency in implementing ETL & ELT data pipelines (with structured or unstructured data) using Apache Kafka, Apache Spark 3.0 and/or Apache Flink 2.0 using the row-/columnar-data model.
- Proficiency in implementing ETL/ELT pipelines into Kubernetes cluster in Azure cloud either as virtual machines or containerized workloads.
- Proficiency in implementing ETL/ELT that stores and retrieves data from object-based data stores (e.g., MinIO) and relational data stores (e.g., PostgreSQL)
- Proficiency in using Grafana, Prometheus, ElasticSearch, Kibana
- Proficiency in programming languages in Java 8+ (e.g., Java 23.x), Kotlin 2.x
- Proficiency in developing performant abstract data structures (e.g., deterministic data lookups versus heuristic data lookups).
- Proficiency with Continuous Integration in using Git-based protocols (e.g., Gitlab, Gitea).
- Proficiency with distributed source code management tools using Git-based protocols (e.g., Gitlab, Gitea).
- Proficiency with using the Linux command line commands (e.g., Linux filesystem, Linux processes).
- Proficiency with integrating OTEL (OpenTelemetry)
- Good communication skills in English
Desirable Skills/Experience
If you have the following desirable skills and relevant experiences, it would be an added advantage!
- Working experiences with Python2/3, Scala2/3.
- Working experiences with working with Event-Driven Architectures.
- Familiar with data serialization & data exchange protocols/technologies (e.g., Apache Avro, FlatBuffers, ProtoBuffers).
- Familiar with cloud-native deployment strategies to cloud service providers (e.g., Azure Cloud, AWS, GCP).
- Familiar with the main cloud service models: Software as a Service, Platform as a Service and Infrastructure as a Service.
Essential / Desirable Traits
- Possess learning agility, flexibility and pro-activity
- Comfortable with agile teamwork and user engagement
At Thales, we’re committed to fostering a workplace where respect, trust, collaboration, and passion drive everything we do. Here, you’ll feel empowered to bring your best self, thrive in a supportive culture, and love the work you do. Join us, and be part of a team reimagining technology to create solutions that truly make a difference – for a safer, greener, and more inclusive world.
