Job Description

We are looking for a skilled Data Engineer to design, build, and maintain scalable data pipelines and cloud-based data platforms. You will work closely with data analysts, data scientists, and software engineers to develop reliable data solutions that support analytics, reporting, and business intelligence initiatives.

Salary Package: Up to $9,000 (Basic, commensurate with experience) + AWS
Working Hours: Mon-Fri
Working Location: Central

Key Responsibilities

Design, develop, and maintain scalable data pipelines using Python and cloud-native technologies.
Build and optimize ETL/ELT workflows to ingest, transform, and process structured and unstructured data.
Develop and manage data lakes, data warehouses, and data integration solutions on AWS.
Ensure data quality, integrity, security, and governance across data platforms.
Optimize data processing performance and troubleshoot pipeline issues.
Collaborate with cross-functional teams to understand business and technical data requirements.
Implement data validation, monitoring, and automated testing for data pipelines.
Support batch and real-time data processing solutions.
Document data architecture, workflows, and technical specifications.
Continuously improve data engineering practices and adopt industry best practices.

Requirements

Bachelor's Degree in Computer Science, Information Technology, Data Engineering, or a related discipline.
Minimum 5 years of experience in Data Engineering or related roles.
Strong programming experience in Python.
Hands-on experience with AWS services such as S3, Lambda, Glue, EMR, Redshift, Athena, ECS/EKS, or Step Functions.
Strong knowledge of SQL and relational databases.
Experience building ETL/ELT pipelines and data integration solutions.
Familiarity with data warehouse and data lake architectures.
Experience with Git and CI/CD practices.
Strong analytical, problem-solving, and communication skills.

Preferred Skills

Apache Spark, PySpark, or Databricks
Apache Airflow or similar workflow orchestration tools
Docker and Kubernetes
Terraform or Infrastructure as Code
Kafka or event-driven data streaming
Snowflake, Redshift, PostgreSQL, or other modern data platforms
Agile/Scrum development methodology

What's Offered

Opportunity to work on large-scale cloud and data transformation projects.
Exposure to modern AWS cloud technologies and data engineering best practices.
Collaborative and fast-paced Agile environment.
Career growth and continuous learning opportunities.

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Elane YapTheng Yu- R1989397

ScienTecConsulting Pte Ltd - 11C5781

Senior Data Engineer (Python/ AWS)