Data Engineer Trainee

Synechron; Singapore; On-site; SGD 42,000 - 60,000; Full time

Benefits offered by this job

Competitive salary

Mentorship

Training program

Career progression

Job summary

Synechron in Singapore is launching an entry-level Data Engineering trainee program. You will join a comprehensive training track covering Databricks Lakehouse, Spark, Delta Lake, and cloud platforms while working on real client data projects.

You will collaborate with cross-functional teams to design scalable pipelines, develop and test ETL/ELT processes, and participate in code reviews and learning sessions under mentorship.

Qualifications

• Recent graduate with a bachelor's or master's in CS, data engineering, information systems, or a related field.
• Strong understanding of computer science fundamentals, including algorithms, data structures, and database concepts.
• Basic knowledge of programming languages such as Python, SQL, or Scala.
• Familiarity with Apache Spark, Databricks, Delta Lake, or cloud platforms (Azure, AWS, or GCP) is a plus.
• Understanding of data warehousing, ETL concepts, and distributed computing principles is advantageous.
• Excellent analytical and problem‑solving skills.
• Strong communication and teamwork abilities.

Responsibilities

• Engage in a comprehensive training program covering the latest technologies in Data Engineering, Cloud Platforms, and the Databricks Lakehouse ecosystem.
• Collaborate with cross‑functional teams to understand client data requirements and contribute to the design of scalable data pipelines and solutions.
• Develop, test, and maintain ETL/ELT pipelines using Databricks, Apache Spark, and Delta Lake in accordance with industry best practices.
• Assist in building and optimizing data ingestion, transformation, and orchestration workflows across structured and unstructured data sources.
• Participate in code reviews, learning sessions, and workshops to continually enhance technical skills in data engineering and cloud technologies.
• Work on real-world data projects that contribute to the success of Synechron's clients, including data modeling, pipeline automation, and performance tuning.
• Support the implementation of data quality checks, governance standards, and monitoring practices within the Lakehouse architecture.
• Receive mentorship from experienced professionals in the field of Data Engineering and Databricks.

Skills

Python

SQL

Scala

Spark

Databricks

Cloud platforms

Communication

Education

Bachelor's or Master's in computer science / data engineering / information systems

Tools

Databricks

Apache Spark

Delta Lake

Job description

Key Responsibilities:

• Engage in a comprehensive training program covering the latest technologies in Data Engineering, Cloud Platforms, and the Databricks Lakehouse ecosystem.


• Collaborate with cross-functional teams to understand client data requirements and contribute to the design of scalable data pipelines and solutions.


• Develop, test, and maintain ETL/ELT pipelines using Databricks, Apache Spark, and Delta Lake in accordance with industry best practices.


• Assist in building and optimizing data ingestion, transformation, and orchestration workflows across structured and unstructured data sources.


• Participate in code reviews, learning sessions, and workshops to continually enhance technical skills in data engineering and cloud technologies.


• Work on real-world data projects that contribute to the success of Synechron's clients, including data modeling, pipeline automation, and performance tuning.


• Support the implementation of data quality checks, governance standards, and monitoring practices within the Lakehouse architecture.


• Receive mentorship from experienced professionals in the field of Data Engineering and Databricks.

Qualifications:

• Recent graduate with a bachelor's or master's degree in computer science, data engineering, information systems, or a related field.


• Strong understanding of computer science fundamentals, including algorithms, data structures, and database concepts.


• Passionate about pursuing a career in Data Engineering and the Databricks/Big Data ecosystem.


• Basic knowledge of programming languages such as Python, SQL, or Scala.


• Familiarity with Apache Spark, Databricks, Delta Lake, or cloud platforms (Azure, AWS, or GCP) is a plus.


• Understanding of data warehousing, ETL concepts, and distributed computing principles is advantageous.


• Excellent analytical and problem‑solving skills.


• Strong communication and teamwork abilities.

What We Offer:

• A dynamic and supportive training environment with a blend of technical learning and hands‑on practical application using Databricks.


• Exposure to cutting‑edge data engineering technology and the opportunity to work on meaningful, large‑scale data projects.


• A clear career path post‑training, with opportunities for advancement in Data Engineering, Cloud Data Architecture, or Analytics Engineering.


• Competitive salary and benefits package.


• A culture that values innovation, inclusivity, and continuous professional development.