Are you an experienced Software Engineer with Big Data Engineering experience and interest/first experience in Cyber Security Data Analysis? Then this role could be your next big opportunity!

On behalf of our client, a globally operating investment bank, Swisslinx is currently searching for a Big Data Engineer who wants to support in the field of Cyber Security Data Analysis. This is a contract role with an initial duration of 6 months with possibility of extension and internalisation after 2 years.

This role will be part of Cyber Security Analytics Data Pump project team. Cyber Security Analytics is a fast-growing team of about 20 people in 3 different regions : Switzerland, US, EMEA (Poland). The Team is responsible for designing, engineering and implementing systems to rapidly process large volumes of data from many disparate sources, providing enhanced knowledge to the bank's security teams and risk functions. This is a global team and Cyber Security Engineers collaborate with teams in all regions and across multiple time zones within
the company.

The mission of the team includes:
- Designing and developing robust, high-volume, streaming security data pipeline services
- Documenting, supporting and maintaining the services

Key Responsibilities:
In this role, you will be mainly responsible for solving highly technical problems, which may require assessing source code to analyse and resolve problems. This requires advanced troubleshooting skills and must be able to adapt and create non-standard approaches to problem-solving.

- Design, develop and test big data solutions
- Create code and configuration to implement product use cases
- Analyse and integrate data from disparate sources
- Analyse and optimize application performance
- Evaluate and identify candidate technologies to meet business needs
- Document test results, designs, and operational manuals for the solutions
- Perform code upgrades
- Identify and document best practices within their subject matters areas of expertise
- Provide continuous process improvement suggestions.
- Provide support for production operations
- Occasional on-duty or after business hours work in case of incident support

Your Profile:
- Experience in Big Data engineering and administration
- Planning, implementing, tuning and scaling big data pipelines from the hardware up.
- Strong experience with some or all of the following: Kafka, Nifi, HDFS and ideally experience with Spark Streaming, Flink
- Experience with one or more of the following programming/scripting languages: Python (preferred), Java, Scala, bash
- Ability to operate comfortably in Linux environments
- Experience with Web APIs, automation and data-related technologies: preferably with REST, JSON, Syslog, TCP, XML, Avro
- Ability to work with network, data centre, and infrastructure teams to optimize the application environment
- Bonus for experience or knowledge of any of the following: Splunk, Salt, MS Azure, Amazon AWS/S3
- Fluency in English

Skills and Qualifications that are a plus:
- Proficient in writing and using REST and SOAP APIs
- Experience with containers, container management (Docker, Kubernetes, Linux Containers)
- Experience working in a DevOps/SRE team, applying Agile methodology
- Experience with assessing incident's criticality and escalation processes
- Experience with writing technical documentation for internal audiences

Do you see yourself in this role? I am looking forward to receiving your CV!
By applying for this position, I consent to the Swisslinx Group of companies:
- storing my personal information (including name, contact details, Identification and CV information etc.) on their internal or external servers for the purpose of informing me of potential employment opportunities
- using my personal information or
- supplying it to third parties upon express consent for the purpose of informing me of potential job opportunities
- transferring where applicable my personal information to a country outside the EEA/EFTA

I also hereby agree to the Swisslinx privacy policy () and Terms of Use ()