Junior Data Engineer (Hybrid)

Automation & Optimization: Assist in implementing automated data quality checks.
Data Warehousing and Modeling: Help develop and maintain data models and warehouse architecture to support data analytics and business intelligence.
Collaboration: Work closely with cross- functional teams, including Data Science, Product, and Software Engineering, to meet business requirements.
Cloud Infrastructure Management: Help manage and optimize data infrastructure components on AWS, utilizing services such as S3.
Machine Learning & AI Integration: Collaborate with Data Scientists and ML Engineers to support the deployment and optimization of ML/AI models.
Data Pipeline Development: Assist in designing, developing, and maintaining data pipelines using Databricks and PySpark to ingest, process, and transform datasets from various sources.

Educational Background: Bachelor&039;s degree in Computer Science, Data Engineering, or a related field.
Experience: 2 years of experience in data engineering, with exposure to DataBricks, PySpark, and AWS.
Technical Skills:
Strong programming skills in Python.
Familiarity with AWS services, particularly S3.
Basic knowledge of Machine Learning frameworks (e.g., TensorFlow, PyTorch).
Proficiency in SQL and relational database design.
Basic proficiency in Databricks and PySpark for ETL processes and data transformation.
Soft Skills:
Good communication and collaboration skills.
Proactive problem- solving abilities and attention to detail.

Preferred Qualifications:

Exposure to real- time data processing frameworks (e.g., Apache Kafka).

Opportunities for professional growth and certifications.
Competitive salary and performance- based bonuses.
Flexible work hours and remote work options.
Collaborative and inclusive work culture.

Cập nhật gần nhất lúc: 2024-11-13 01:25:03