Big Data Platform Engineer # 100398

We are seeking talented, experienced big data engineer to join a growing, high-visibility cross-Bank team that is developing and deploying solutions to some of Credit Suisse’s most challenging analytic and big data problems. As a member of this team, you will work with clients and data spanning Credit Suisse’s global organization to solve emerging mission-critical challenges via the utilization of new technologies such as:

  • Distributed file systems and storage technologies (HDFS, HBase, Accumulo, Hive)

  • Large-scale distributed data analytic platforms and compute environments (Spark, Map/Reduce)

  • Tools for semantic reasoning and ontological data normalization (RDF, SPARQL, Tamr)

  • A hands-on engineering position responsible for supporting client engagements for Big Data engineering and planning

  • A solid platform for you to drive the engineering/design decisions needed to achieve cost-effective and high performance result

  • You will be part of a global team of Big Data engineers who are engineering the platform and innovating in core areas of big data, real time analytics and large-scale data processing

Credit Suisse maintains a Working Flexibility Policy, subject to the terms as set forth in the Credit Suisse United States Employment Handbook.

  • A formal background and validated experience in engineering, mathematics and computer science, particularly within the financial services sector

  • Hands on Programming / Scripting Experience (Python, Java, C/C++, Scala, Bash, Korn Shell)

  • DevOps Tools (Chef, Docker, Puppet, Bamboo, Jenkins)

  • Linux / Windows (Command line). An understanding of Unix/Linux including system administration and shell scripting

  • Proficiency with Hadoop v2, MapReduce, HDFS

  • Management of Hadoop cluster, with all included services

  • Good knowledge of Big Data querying tools, such as Pig, Hive, and Impala

  • Data Concepts (ETL, near-/real-time streaming, data structures, metadata and workflow management)

  • You will have the ability to function within a multidisciplinary, global team. Be a self-starter with a strong curiosity for extracting knowledge from data and be able to elicit technical requirements from a non-technical audience

  • Collaboration with team members, business partners and data SMEs to elicit, translate, and prescribe requirements. Cultivate sustained innovation to deliver exceptional products to customers

  • You should have experience with integration of data from multiple data sources

  • Strong communication skills and the confidence to present deep technical findings to a business audience

For more information visit Technology Careers