Credit Suisse - Vice President - Data Engineer

We Offer

You an exciting and global environment to work with the Data Analytics team within Internal Audit (IA), to apply your technical skills to help analyses large data sets and databases to support the IA team to lead and perform data analytics.

- Collaborate with the data owners to ensure that the data sourced/used follows the compliance, access management, bank's control policies, and that it meets the qualification and assurance requirements of the department.

- Apply and build data analytics tests based on walkthroughs with the audit team, including crafting requirements as well as performing the necessary analytics.

- Apply conceptual thinking through synthesis of facts, theories, trends, inferences, and key issues and/or themes in complex and variable situations, to solve a diverse range of business problems.

- Diagnose problems from multiple angles, using formal problem - solving tools and techniques

- Seek out opportunities to improve, streamline, reinvent work processes through data driven solutions. In addition, explore and evaluate numerous potential solutions, maintaining balance between innovation and pragmatism when figuring out the best approach.

- Demonstrate personal dedication to change through actions and words, and mobilize others to support change through times of stress and uncertainty

- Display your good communication through conversing with, writing strategic documents and creating/delivering presentations to internal and external partners.

- Consistently foster teamwork and respect among team members by addressing elements of the group process that impedes, or could impede the group from reaching its goal.

- Educate the organization both from data and analytics perspectives on new industry/technology approaches and developments, such as testing hypotheses and statistical validation of results.

- Dedicatedly engage Internal Audit team to find opportunities to leverage technology and analytics in connection with risk assessment and audit execution processes.

- The role is open to flexible/agile working arrangements.

You Offer

Required

- Experience on: Bash (essential), Python (essential). Excellent grasp on Unix shell scripting is essential.

- 8+ years- experience in enterprise IT at a global organization. Recent 5+ years hands on experience in Big Data ecosystem software development

- Strong experience on Hadoop, (Hive or Impala), SQOOP, KAFKA, map reduce programming. Knowledge of HDFS formats and structure like Parquet, Avro, etc.

- Understanding of security principles e.g. SSL, Kerberos

- Experience of integrating with existing strategic Big Data Platform components (basically Cloudera HDFS with Spark, Python etc)

- Experience of loading data from different datasets and deciding on which file format is efficient for a task. Source large volumes of data from diverse data platforms into Hadoop platform

- An ability to construct end-to-end data analytic workflows including data capture, cleaning, normalization, exploration, modeling and visualization, preferably utilizing the tools previously described

- Experience of fine tuning Hadoop applications for high performance and throughput.

- Experience on ETL tools such as Informatica or Pentaho DI

- Understanding the requirements of input to output transformations. Define Hadoop Job Flows. Translate complex functional and technical requirements into detailed design

- Troubleshoot and debug any Hadoop ecosystem run time issues.

- 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

- Work in teams and collaborate with others to clarify requirements

- Assist in documenting requirements as well as resolve conflicts or ambiguities

- Good attention to detail around documentation

- Process oriented and proactive individual with a solution-driven attitude

- Strong communication skills and the ability to present deep technical findings to a business audience

- Fluent written and spoken English

Additional Skills

- A formal background and proven experience in mathematics, statistics and computer science, particularly within the financial services sector. Experience within related fields such as physics, chemistry or biology will be considered

- Experience with distributed computing environments such High Performance Computing (HPC) systems and an understanding of parallel application performance and reliability.

- Experience deploying software within a large enterprise environment (agile or associated development methodologies, back testing, release management, JIRA)

- An understanding of Unix/Linux including system administration

- Experience of tuning Hadoop solutions to improve performance and end-user experience

- Integration with Tableau a plus

- Environment and Production support experience will be an advantage, Experience on security tools such as sentry will be desirable.

- Database management and business intelligence including SQL, data modeling or schema management. Experience with NoSQL database such as Marklogic will be an added advantage.