SOCOTEC VIETNAM is a technical support platform for the SOCOTEC GROUP providing expert services on a range of projects in testing, inspection and certification (TIC) in the construction and infrastructure sectors. Around the globe, more than 15,000 experts in 26 countries across 5 continents deliver professional services in construction, buildings & real estate, infrastructures, environment & safety and certification.
We are currently expanding our SOFTWARE & IT SERVICES team and are looking for a Senior Data Engineer to join our growing team and help deliver high-quality projects to our client
Job Description- Develop end-to-end data pipelines (ingestion, transformation, modeling, exposure) and contribute to the implementation of visualizations in Power BI or Databricks SQL.
- Continuously improve the SOCOTEC Lakehouse, particularly in the areas of governance, quality, and data pseudonymization.
- Experiment with generative AI solutions applied to data, such as Databricks GenIE, to transform text queries into actionable insights.
Qualifications- Bachelor's degree in Big Data, Computer Science, or Software Engineering with a strong specialization or appetite for data and distributed architectures. At least 3 years of experience in Data Engineering
- Strong mastery of SQL and NoSQL databases (modeling, optimized queries, integrity, and performance).
- Good understanding of Big Data architecture and distributed processing tools (Spark, Hadoop, Airflow, Kafka, Delta Lake, etc.).
- Prior experience with Databricks would be appreciated.
- Good communication skills in English or French.
- Experience with collaborative development environments: Git, GitLab, Jupyter Notebooks, VS Code
- Valued knowledge of AWS cloud services.
- Familiarity with ETL/ELT principles, Data Lakehouse, and DataOps (CI/CD, monitoring, data quality).
- Interest in emerging technologies, particularly Generative AI and its integration into Data platforms.
- Team spirit, rigor, and sense of collaboration in an agile environment.
- Technical curiosity and ability to quickly learn new tools and paradigms.
- Autonomy, service-oriented mindset, an
Additional Information- Attractive salary and bonus with annual revision.
- 42 hours per week (30 minute early finish every Friday), flexible working hours options
- 15 annual leave days (Women) & 13 annual leave days (Men) - increasing with length of service & seniority, 15 working from home days each year
- Team-building activities, Sport Clubs
- Cooperation with colleagues around the world in a leading global group
- Strong team spirit in an entrepreneurial environment of a growing company
- People values, social responsibility, and sustainability.
- Opportunities for self-development and career advancement
- Internal training courses (technical, foreign language, soft skills)
Skills Required
- Bachelor’s degree in Big Data, Computer Science, or Software Engineering
- At least 3 years of experience in Data Engineering
- Strong proficiency with SQL and NoSQL databases, including modeling, query optimization, integrity, and performance
- Understanding of Big Data architecture and distributed processing tools such as Spark, Hadoop, Airflow, Kafka, and Delta Lake
- Good communication skills in English or French
- Experience with Git, GitLab, Jupyter Notebooks, and VS Code
- Familiarity with ETL/ELT, Data Lakehouse, DataOps, CI/CD, monitoring, and data quality
- Interest in Generative AI and its integration into data platforms
- Prior experience with Databricks
- Knowledge of AWS cloud services
- Teamwork, rigor, autonomy, service orientation, and ability to learn new tools quickly
What We Do
SOCOTEC is a leading international provider of testing, inspection, certification, and consulting (TIC) services. The company ensures the integrity and performance of assets and the safety of people throughout the entire life cycle of built assets. With a focus on construction, infrastructure, and industry, SOCOTEC provides technical expertise and advisory services to help clients manage risks and improve technical, energy, and environmental performance.
