Job Description :
Big Data Engineer
We Offer.
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, the successful candidate 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 the candidate 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
The candidate 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
You Offer.
A formal background and proven experience in engineering, mathematics and computer science, particularly within the financial services sector
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
Proficiency with Hadoop v2, MapReduce, HDFS, Spark
Management of Hadoop cluster, with all included services
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)
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
Experience with integration of data from multiple data sources
Strong communication skills and the ability to present deep technical findings to a business audience