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Found the message below in my mailbox today. Is such a high salary possible? The subject line was "$320,000 Java architect/developer with Cloud computing and Big Data experience". Here's the message (anonymized by respect for the recruiter). I added the picture myself.

I am a recruiter seeking Java architect/developers with Cloud Computing and big data expertise.  If you know anyone who would like a $300k-$320k job, please have them call me if they have a similar profile like the one below.  Thank you.   If you have friends in California with Java development experience with Big Dat and Cloud Computing there are so many $200k-250k jobs in the California area also.

Honors and Awards:

  • CFA Level III  Passed
  • AWS Certified Solutions Architect – Associate
  • Cloudera Certified Developer for Apache Hadoop
  • Cloudera Certified Administrator for Apache Hadoop
  • Sun Certified Enterprise Architect
  • Oracle Database 10g Administrator Certified Professional
  • IBM Certified Application Developer – DB2 9
  • Cloudera Certified Administrator for Apache Hadoop

Skill Summary

  • Domain Knowledge: Strong background on building financial system. (CFA level III passed).
  • Architecture Design: Excellent knowledge of architecture design, development and best practices. Excellent on converting business requirements into technical solution. Good at communicate complex technical concepts to non-technical people.
  • BIG DATA and Cloud: Hadoop, Amazon Web Service, Mapreduce, Pig, Spark, Hive, Hbase,  DynamoDB, etc.
  • Core Java and J2EE: Core java (multi-threaded, NIO, performance turning, etc). Traditional Java framework (Struts 1.1, EJB 1.1, etc) and lightweight approach: Spring, Struts (Webwork) and Hibernate.
  • Database Development: Oracle, SQL Server, Mysql, firebird, etc. Familiar with ORM mapping framework: Hibernate and JDO (Castor JDO).
  • Other Technical Skills: Corba, RMI, SOAP, Portal and Wiki (Confluence), ETL (Kettle), Ajax, Packaging and Deployment (NSIS), Visual Basic, POI, Excel, Flex, XML, etc.

Here's another job ad that I received a few days ago from David Young, VP of Analytics at MarketShare. It probably commands a salary well above $200K:

Business Title: Global Leader – Internet Mktg Analytics

Subsidiary: eBay

Primary Job Responsibilities: We’re looking for a seasoned global marketing analytics leader to join our team. This person must be based in Seattle, Washington to lead our global internet marketing analytics team. S/he will be the senior marketing analytics advisor to the global internet marketing team. Specific responsibilities are:Lead, mentor and coach to a global team of marketing analysts and data scientistsBuild trusted relationships with key regional and global executives (GM, CFO, CMO etc.) and their delegates to drive analytical learnings into business decisionsBe the trusted business partner and enabler of clear data driven business decisions across a matrix spanning business units, countries, regions and geographiesUp-level analytical answers into stories that are easily consumable by an executive audienceDrive insights that will affect the global marketing-mix at the country and region level; champion the current model and future evolutions to measure and to improve marketing return on investment across channelsAnswer ad-hoc questions from executives regarding marketing effectiveness, conduct root-cause analysis, and provide recommendations for changeJob Requirements: MBA or Master/PhD in social science, hard science, mathematics, statistics or related fields or 10+ years of directly applicable work experience
Success managing global marketing analytics teams and managing executive stakeholders

Last Updated: 04/21/2015

Link to apply

I also discussed a chief data scientist position directly with Microsoft a few months ago, and mentioned that I'm out of the market as I am over-priced and working from home. I casually said "I suppose this is not paying more than $200K" and the answer, from the hiring manager, was "several times that amount". The job was a good fit for a senior data scientist with a good operations research background.

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