- Raleigh, NC, USA
- Permanent, Full time
- Credit Suisse -
- 20 Aug 18
Big Data Engineer # 115238
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 emerging 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).
The role offers:
- 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.
- Thinking out of the box on improvements to current processes & enhancing existing platform.
- 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.
- You have a formal background and proven experience in engineering, mathematics and computer science, particularly within the financial services sector.
- You have hands on Programming/Scripting Experience (Python, Java, Scala, Bash).
- DevOps Tools (Chef, Docker, Puppet, Bamboo, Jenkins).
- Linux/Windows (Command line). An understanding of Unix/Linux including system administration and shell scripting.
- You gave proficiency with Hadoop v2, MapReduce, HDFS, Spark.
- Management of Hadoop cluster, with all included services.
- You have good knowledge of Big Data querying tools, such as Pig, Hive, Impala and Spark.
- Data Concepts (ETL, near-/real-time streaming, data structures, metadata and workflow management).
- You have the ability to function within a multidisciplinary, global team. Be a self-starter with a strong curiosity for extracting knowledge from data and the ability to elicit technical requirements from a non-technical audience.
- Collaboration with team members, business stakeholders and data SMEs to elicit, translate, and prescribe requirements. Cultivate sustained innovation to deliver exceptional products to customers.
- Do you have experience with integration of data from multiple data sources?
- Do you have strong communication skills and the ability to present deep technical findings to a business audience?
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