Data Engineer (Hadoop & Spark)

Job Description

We are on the lookout for a skilled Data Engineer with proficiency in Hadoop and Spark to join our data engineering team. The suitable candidate will be responsible for designing and implementing data pipelines, ensuring data quality, and enhancing our data processing capabilities.

Responsibilities

• Develop and manage data pipelines that ensure efficient data flow.
• Collaborate with cross-functional teams to enhance data infrastructure.
• Utilize Spark for batch processing and real-time data streaming applications.
• Maintain and optimize existing data systems for improved performance.
• Conduct code reviews and provide mentorship to junior engineers.
• Implement data governance policies to ensure compliance and security.
• Evaluate new data technologies and recommend improvements to our stack.

Requirements

Education

• Bachelor's degree in Data Science, Computer Science, or equivalent
• Master's degree preferred

Experience

• 5+ years of experience in data engineering and analytics

Technical Skills

• NoSQL Databases
• Data Visualization

Soft Skills

• Problem Solving
• Critical Thinking

Certifications

• Google Cloud Professional Data Engineer
• Microsoft Certified: Azure Data Engineer Associate

Languages

• English: Fluent

Advantageous

• Knowledge of machine learning concepts: Basic understanding of machine learning principles to support advanced analytics.
• Experience with Apache Kafka: Familiarity with message streaming platforms for building data pipelines.

Benefits

• Comprehensive health insurance packages
• Generous retirement plan with matching contributions
• Flexible schedules with remote work opportunities
• Employee assistance programs

Company Culture

• Innovation: We prioritize innovation and encourage creative thinking and problem-solving.
• Growth Mindset: Our organization fosters a growth mindset, encouraging employees to learn and evolve.
• Inclusivity: We strive to create a work environment where every voice is heard and respected.