Kafka Engineer for Operational Data Lake

CFO Office is responsible to increase Swedbank’s efficiency and quality and ensure coherent and easily understood financial steering. CFO Office is also responsible for ensuring adequate and credibile management information.

Swedbank is the bank for the many. As an employer we favour inclusion, support workforce diversity and are leading in gender equality. We welcome all applicants regardless of gender, ethnicity, religion or other conviction, age, gender identity or expression, sexual preference, or disability. To find out more about Swedbank as an employer, visit swedbank.com/work-with-us

About the job Swedbank is increasing its analytical capabilities and diversifying its data landscape, looking at new ways of capitalizing on data, with the ultimate goal of better knowing and hence better serving our customers. In doing this, new platforms and technologies for discovery, advanced analytics and big data will be explored and introduced. This will be done in close cooperation with the business and IT.

As a Kafka Engineer in the ODL Platform team, you will work within the Data Discovery & BI Architecture Value Stream in CFO's Group Business Intelligence department.
You will have an important role in a Cross Functional Team (CFT) working with use cases (UC). You will work both independently and in close cooperation with other team, consisting of data engineers, data scientists and BA.

You will be engaged in:

Establishing a solid operation and maintenance of our Kafka implementation
Designing and building streaming solutions with Kafka (KSQL,KStream)
Requirement analysis together with stakeholders
Technical design of streaming and event integration
Micro service oriented way of working
Automation of software installation and configuration
Third line support of our Data Lake platform


What you need to succeed As a Kafka Engineer in Data Platform team, we expect you to have experience in a wide range of technologies. Programming is expected to be mostly in Java, Groovy, Python, and UNIX shell scripting. Kafka and Hadoop is the core platform; you also need experience in DevOps automation preferable with Ansible.

You have a solid combination of the following requirements:

Eger to learn new technology
Database knowledge for SQL querying and retrieving the data
UNIX Operating system and commands' understanding
Jenkins knowledge
Ansible
Docker and how to build docker based services for Analytical use cases
Security (TLS) and kerberos


An extra meriting would be knowledge in:

Building High Available for business critical applications
Automation framework development
GIT
Experience of Hadoop echo system in high available implementations
Experience and knowledge in Data Analytics and AI


As a person, we expect you to have readiness and interest in learning and keeping yourself up to date with new technologies and platforms. You are a team-player and ready to excel within your area of expertise. We expect you to have good communication skills, both verbally and in written, also excellent in English.

What you may have worked with previously system analyst
lead data engineer
senior data scientist


Why work with us? In our team we have an open and transparent atmosphere. We believe in giving a lot of freedom paired with the corresponding level of responsibility and accountability. We expect a self-going working style towards agreed goals and we all contribute to creating a positive and collaborative working environment

A good, easy-going and positive working climate and a constructive and collaborative attitude within our team and with our colleagues we believe are the keywords to success. We expect everyone in the team to be able to cooperate with a positive and open mind, be respectful of other's competence, be willing to share experience and knowledge when asked to and also to be open to learning new things and be ready to challenge and change old ways of doing things.

 

We may begin the selection under the application period, so we welcome your application as soon as possible.

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