Job Description
Description: He/she will work closely with lead developers, architects and data/business analyst. This person will implement, test and document as needed. Occasionally the developer will be client interacting, he/she should feel confident publicly speaking and explaining technical configurations. This person will also work with the client relations and project management teams insuring the SpectraMedix product is meeting the highest standards of quality and satisfying its customers.
Desired: - 4 - 6 years of experience with a bachelor degree in any engineering or equivalent technical / quantitative field.
- Excellent analytical and problem-solving skills
- Good understanding of data structures and algorithms
- Good problem-solving ability
- Must have understanding of design patterns
- Excellent knowledge of object-oriented programming
- Strong knowledge of version control systems
- Hands on experience of using Netbeans/Eclipse
- Should be able to complete the task with less supervision.
Required Technical Expertise: - Core Java (OOPS)
- Big Data Ecosystem
- Spark ,
- Spring Framework
- SQL
- J-Unit
Required Candidate profile
* At-least 1 y into Java.
* Experience in Spark should be at-least 2 y.
* Someone who has worked in Spark with Java language will be a plus.
* Someone who is willing to work in Spark with Java.
* Should be good in Spark.SQL, Spark optimization, Spark data processing, Spark streaming.
Job Classification
Industry: IT-Software, Software Services
Functional Area: IT Software - Application Programming, Maintenance,
Role Category: Programming & Design
Role: Programming & Design
Employement Type: Full time
Education
Under Graduation: B.Tech/B.E. in Any Specialization, BCA in Computers
Post Graduation: MCA in Computers, M.Tech in Any Specialization
Doctorate: Doctorate Not Required
Contact Details:
Company: SpectraMedix
Location(s): Noida, Gurugram
Website: https://www.spectramedix.com/
Keyskills:
hive
big data developer
performance tuning
spark developer
datasets
spark core
spark optimization
spark sql
spark streaming
rdd
dataframes
apache spark
hadoop
spark ML