Building large cloud based systems requires good engineering. Especially if this involves the BigData Processing and Real Time Analysis. This is also a fast moving technology space. An Architect in this domain should see above and beyond the business requirements anticipating future changes. He should be well versed with the current solution design and keep track of the latest trends in the technology and tools used in this space.

The Data Architect

dataarchitect

A Data Architect would be required to design products which requires careful integration of these skill sets.

  1. Data Science
  2. Big Data
  3. Cloud
  4. App Development

A Data Architect could also be a Research Engineer, Solution Architect or a CTO of company building data intensive applications.

Each of these areas are vast in themself. However based on our interest and experience we would have a narrow range of specialization and can branch off from their when ever required in future.

These are the areas of my experience:

Data Science

  • NLP, Machine Learning, Predictive analysis
  • Data Visualization
  • Languages: R, Python, Scala

Big Data

  • Hadoop, Spark, Hive, Sqoop
  • Cassandra, MongoDB, OLAP and Relational Databases
  • Kafka, Zookeeper and distributed systems
  • Chef Vagrant, Docker and Automation

Cloud

  • Certified AWS Solution Architect
  • S3, ELB, Lambda, SNS, CloudFormation
  • Redshift, EMR and RDB
  • Cloud Security and VPC

App Development

  • Languages: Scala, Python, Javascript
  • Microservice Architecture and Reactive Apps
  • Continous Integration and Automation

I write around these areas of my interest.

This is the IntelliSignals blog. The source code for the various code snippets can be found at github repo eellpp