Big Data

Position Overview:

Big Data Engineer

Key Responsibilities:

• Design and implement

  Big Data solutions

  leveraging

  Hadoop

  ,

  Apache

  , and

  OpenStack

  technologies.
• Develop and optimize distributed

  data processing

  solutions using

  Hadoop MapReduce

  and other

  big data frameworks

  (e.g.,

  Pig

  ,

  Hive

  ,

  Mahout

  ).
• Work with

  NoSQL databases

  (e.g.,

  HBase

  ,

  Cassandra

  ) to handle large-scale data storage and retrieval.
• Architect, design, and implement scalable

  distributed computing

  solutions using

  Java

  programming.
• Collaborate with cross-functional teams to understand requirements and implement big data pipelines that process vast amounts of structured and unstructured data.
• Perform hands-on

  coding

  and development of solutions in

  Java

  to meet the growing demand for big data processing.
• Leverage

  open-source tools

  like

  Apache Spark

  ,

  Kafka

  , and others to enhance performance and data processing capabilities.
• Contribute to the design and architecture of

  cloud-based solutions

  , ensuring high availability, scalability, and performance.
• Perform

  testing

  of developed products, ensuring they meet the functional, performance, and reliability requirements.
• Work in a

  virtualized environment

  to optimize product development and ensure seamless integration with cloud technologies.
• Monitor and optimize

  big data systems

  , ensuring maximum efficiency and stability.

Key Skills & Qualifications:

• Strong experience in

  Big Data frameworks

  , such as

  Hadoop

  ,

  Pig

  ,

  Hive

  ,

  Mahout

  , and

  OpenStack

  .
• Hands-on experience with

  NoSQL

  databases (e.g.,

  HBase

  ,

  Cassandra

  ,

  MongoDB

  ).
• Expertise in

  distributed computing

  and

  data processing

  with

  Hadoop MapReduce

  using

  Java

  programming.
• Proficiency in

  Java

  programming for developing and optimizing big data solutions.
• Experience with

  cloud technologies

  and

  virtualization

  in a distributed computing environment.
• Strong understanding of

  networking

  concepts and how they apply to cloud-based systems and big data.
• Familiarity with

  Apache Spark

  ,

  Kafka

  , and other complementary big data tools.
• Experience in designing and deploying

  cloud-based architectures

  , including multi-cloud and hybrid cloud models.
• Excellent problem-solving skills and the ability to work with complex data processing and storage requirements.