Data Engineer

Responsibilities

Develop and maintain

ETL/ELT pipelines

for collecting, transforming, and processing data.

Write efficient

SQL queries

for data extraction, transformation, validation, and analysis.

Develop data processing scripts and utilities using

Python

.

Work with relational and NoSQL databases for data storage and processing.

Perform data validation, cleansing, and troubleshooting to ensure data quality.

Support integration of data from multiple sources into centralized data platforms.

Work with cloud platforms such as

AWS, GCP, or Azure

.

Monitor data pipelines and troubleshoot failures or data-related issues.

Collaborate with software engineers, analysts, and other technical teams on data requirements.

Follow engineering best practices for version control, testing, documentation, and deployment.

Qualifications

Bachelor's degree in

Computer Science, Information Technology, Engineering, or a related field

.

Strong programming fundamentals in

Python

.

Good understanding of

SQL

and relational databases.

Understanding of

ETL/ELT concepts and data pipelines

.

Familiarity with databases such as

MySQL, PostgreSQL, Oracle, MongoDB, or similar

.

Basic understanding of at least one cloud platform:

AWS, GCP, or Azure

.

Familiarity with

Git/version control

.

Strong problem-solving and analytical skills.

Good to Have

Exposure to

PySpark, Apache Spark, Pandas, or NumPy

.

Experience with cloud services such as

GCP, AWS, or Azure

.

Exposure to

Docker, CI/CD, or Linux

.

Experience working with APIs and data integration.

Academic, internship, or personal projects involving

data engineering, data pipelines, databases, or cloud technologies

.

(

Note:

Relevant applicants will receive an email requesting additional information as part of the next stage. The application process will be completed directly on the team's designated platform, and all subsequent communication and decisions regarding the opportunity are managed by the respective hiring team.)