Data Engineer

We're looking for Data Engineers!
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.)

Work arrangement
Hybrid