Senior Data Engineer (Hadoop)

Job Description:

• 8+ years of experience in web, Hadoop/data processing, distributed systems, and/or large-scale databases.
• Knowledge of  Oozie, Spark, Python, and SQL queries
• Knowledge of Google Cloud Platform/AWS, Airflow, and Data Batch  and streaming processing
• Knowledge on building ETL Data pipeline, performance, and handling a large set of data 
• Knowledge of backend  Java /Scala
• Experience with container and cloud technologies such as Kubernetes, Docker, Evnet driven mechanism
• Very good at problem-solving and DS
• Excellent verbal and written communication skills
• Self-motivated and able to work independently.

Job Responsibilities:

• Engage with teams to define requirements/interfaces/implementation approaches
• Exercise agile development methodologies to create platform services and features
• Collaborate with other engineers to write testable, reliable code, continuously deploying to production systems
• Build large-scale distributed systems that balance resources, constraints, requirements, and complexity
• Drive design, development, and delivery of key components of platforms & services.
• 8+ years of experience in web, Hadoop/data processing, distributed systems, and/or large-scale databases.

Education: Bachelor’s or Master’s degree in Computer Science, Computer or Electrical Engineering, Mathematics, or a related field.

GlobalLogic estimates the starting pay range for this role to be performed in Remote to be $110,000 to $120,000 and reflects base salary only. This pay range is provided as a good-faith estimate, and the amount offered may be higher or lower. GlobalLogic takes many factors into consideration in making an offer, including candidate qualifications, work experience, operational needs, travel and onsite requirements, internal peer equity, prevailing wage, responsibilities, and other market and business considerations.