Application Development Lead - Finance Big Data Platform
We Offer Job Overview
A senior Data Engineer to join our growing team of analytics experts in Finance Data hub In the Product Control IT department in Credit Suisse .The hire will be responsible for expanding and optimizing our data and data pipeline architecture, as well as optimizing data flow and collection for multi-functional teams. This is a leadership role, which is also focusing on resource management, driving governance and standards through the wider team Job Responsibilities
Credit Suisse maintains a Working Flexibility Policy, subject to the terms as set forth in the Credit Suisse United States Employment Handbook. You Offer
- You're role would support our software developers, database architects, data analysts and data scientists on data initiatives and will ensure optimal data delivery architecture is consistent throughout ongoing projects.
- Self-directed and comfortable supporting the data needs of multiple teams, systems and products.
- You should be excited by the prospect of optimizing or even re-designing our company's data architecture to support our next generation of products and data initiatives.
- You will assemble large, complex data sets that meet functional / non-functional business requirements.
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL, Sqoop , file based and Kafka.
- Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.
- Work with partners including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Keep our data separated and secure across national boundaries through multiple data centers.
- 5+ years of experience in a Data Engineer role, who has attained a Graduate degree in Computer Science, Statistics, Informatics, Information Systems or another quantitative field. They should also have experience using the following software/tools:
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- Experience with relational SQL and NoSQL databases, including Postgres and Cassandra is optional .
- Experience with stream-processing systems: Storm, Spark-Streaming, etc.
- Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
- You should be an experienced data pipeline builder and data wrangler who enjoys optimizing data systems and building them from the ground up.
- You have advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.
- You have experience building and optimizing 'big data' data pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and seek opportunities for improvement.
- You possess strong analytic skills related to working with unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- You have a successful history of manipulating, processing and extracting value from large disconnected datasets.
- You have working knowledge of message queuing, stream processing, and highly scalable 'big data' stores.
- You have strong project management and interpersonal skills.
- Experience in supporting and working with multi-functional teams in a dynamic environment
- Your experience with Cloud and Data Science tools such as R and Python is optional