Junior Data Engineer

JOB SUMMARY:

We're looking for a Data Engineer with strong software engineering fundamentals to build and scale our data infrastructure. You'll design high-performance systems that handle massive data volumes and high-concurrency workloads, optimize query engines for speed and reliability, and architect robust data pipelines. This role is for engineers who love solving distributed systems challenges and building production-grade infrastructure that processes terabytes of data daily.

This role is open to fresh graduates and early-career professionals (1–2 years of experience) who are eager to grow their skills in building scalable data systems.

Whether you’re just starting out or already have some experience, this is a great opportunity to develop your data engineering skills and contribute to impactful, data-driven decision-making.

KEY RESPONSIBILITIES:

Design, develop and maintain data infrastructures, such as computation, query engine and services which can support massive data and high concurrency requests

Clean, transform, and optimize raw data for storage and analysis

Work with structured and unstructured data from various sources (databases, APIs, files, etc.)

Plan data warehouse structure to ensure data quality, accuracy, consistency, and availability

Optimise for the performance of the data pipeline and service to downstream

Collaborate with business analysts, data scientists, and backend teams to provide appropriate tools

Document data models, processes, and technical decisions

What You'll Learn:

Real-world data engineering with modern tools like Apache Spark/Flink, Kafka, Airflow

Working with SQL/NoSQL databases, data lakes, and cloud platforms (AWS, GCP, Azure)

Building batch and streaming data pipelines

Data modeling, warehousing

Orchestration and monitoring of data workflows

Developing high availability services

Best practices in data governance, privacy, and security

Collaboration in agile, cross-functional teams with product, engineering, and analytics

JOB REQUIREMENTS:

For Fresh Graduates

Bachelor’s degree in Computer Science, Data Engineering, Software Engineering, or a related field (or graduating soon)

Good understanding of at least one programming language (Java, Python, C++, Golang)

Good knowledge and able to work with SQL

Solid understanding of computer science fundamental knowledge (system, network)

Exposure to big data concepts through coursework, internships, or projects

Eagerness to work with large datasets and cloud-based data platforms

Willingness to learn new tools and follow team best practices

For 1–2 Years Experience

1–2 years of experience in data engineering and backend development

Proficient in Java or Python development with demonstrated project experience

Familiar with SQL, understand the performance and optimization

Familiar with big data related tech stacks (eg. Spark, Flink, Iceberg, Hadoop, Hive) and data pipeline design

Experience with cloud services (eg. S3, Cloud Functions, Kubernetes)

Able to troubleshoot data issues and build scalable data solutions

Nice to Have (For All Levels):

Experience with data orchestration tools (Airflow, Prefect, Dagster, etc.)

Familiarity with big data tools (Spark, Kafka, Hadoop)

Exposure to data visualization tools (e.g., Looker, Tableau)

Understanding of CI/CD, containerization (Docker), and infrastructure-as-code

Contributions to personal or open-source data projects

Knowledge of data privacy and compliance (GDPR, HIPAA, etc.)

Soft Skills:

Passionate on techniques and real-world problem solving

Team player with good communication skills

Open to feedback and continuous improvement

Responsible and proactive in solving data challenges

Eagerness to explore new tools and share knowledge

What We Offer

Structured onboarding and mentorship to grow your data skills

Opportunities to work on real-world data systems with production impact

A collaborative, knowledge-sharing team culture

Clear growth paths toward analytics engineering, senior data engineering, or data platform roles