Junior Data Engineer

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

Benefits

Additional Information

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.

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