Data Engineer

Qualifications

  • Advanced degree in computer science, information systems, or closely related field
  • 1-5 years of hands-on experience in software engineering or IT infrastructure role
  • Advanced knowledge of Hadoop stack, with prior experience in Hive, Pig, HBase, Impala and Sqoop
  • Advanced knowledge of object oriented programming, distributed systems and software design principles
  • Advanced knowledge of database maintenance and administration using MS SQL Server
  • Strong programming experience in Java, Python and R
  • Hands-on experience in Microsoft Azure or Amazon EC2 cloud platform
  • Demonstrated ability to design and implement ETL workflows across both Windows and Linux environments
  • Should be a highly motivated individual with the ability to work effectively with people across all levels in an organization
  • Position requires ability to travel about 20%
  • Programming experience in C++, SAS, and JavaScript
  • Experienced in RDBMS systems like Oracle Database, IBM DB2, or MySQL
  • Experienced in NoSQL systems like MongoDB, Redis, or Cassandra
  • Experienced in Apache Spark

Who You'll Work With

You'll work with our Analytics group in Waltham, Massachusetts, co-located with our Knowledge Center colleagues. As a member of this team, you'll work with McKinsey consulting teams to carry out complex data analysis and modeling, creating a foundation for sound recommendations for client studies and internal projects.

What You'll Do

You will expand McKinsey's current analytics and machine learning capabilities, helping create new strategies and data tools within an innovative organization. You will help shape the future of what data-driven organizations look like, creating new lines of thinking within a diverse range of clients and situations. You will constantly engage with our clients and team members as they architect new systems and strategies for extracting, transforming and optimizing data flows from complex, sometimes disparate, data sources. You will work with our clients' entire data ecosystem to enable effective, highly scalable data analysis pipelines. This role will develop, implement and maintain distributed systems around all elements of data analysis with a constant eye toward continuous improvement.


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