Data Engineer  

Design, build, and maintain scalable, secure data pipelines and storage systems; ensure data quality through ETL processes and regular checks.

Implement policies and practices to control, optimize, and secure data assets, ensuring data integrity and accessibility.

Develop and maintain data models, structures, and databases to meet business needs; communicate data architecture effectively.

Develop, test, and maintain scripts and programs to automate data processing and pipelines, adhering to industry standards.

Create and operationalize data visualization solutions to simplify complex data for stakeholders and decision-making.

Work with cross-functional teams to gather data requirements, optimize existing processes, and deliver ad hoc reports and insights

At least graduate with a Bachelor’s or Master's Degree in IT, Computer Science, Engineering, or any related course.

At least 3 years of experience in data engineering, data analytics, or related fields.

• Hands-on experience with data manipulation tools (e.g., pandas, dplyr, or Spark).

• Proficiency in Extract, Transform, and Load (ETL) processes for efficient data pipeline management.

• Expertise in both SQL and NoSQL query languages for database interaction and management.

• Experience with big data storage and processing solutions, such as MongoDB, Spark, Hive, Snowflake, Redshift, or similar technologies.

• Experience with cloud-based or server-based data processing environments (e.g., AWS, Azure, GCP).

• Proficiency in Python and Java, with experience in other programming languages is a plus.