Job Description

Company Description

About Us

RepRisk is the world's most respected Data as a Service (DaaS) company for reputational risks and responsible business conduct. Our mission is to provide transparency on business conduct risks to drive positive change. Combining advanced AI with deep human expertise, and a proven methodology at the core, RepRisk's solutions bring performance and peace of mind, enabling clients to know more, be sure, and act faster. With our values of intellectual honesty and humility, operational excellence, and openness and respect, our diverse teams of talented experts are pioneering solutions that enable clients to make better informed decisions. Headquartered in Zurich, and with offices in Toronto, New York, London, Berlin, Manila, and Tokyo, we stay close to clients and bring an independent lens to the industry. United by our shared belief in the power of data, our 400 people are proud to be setting the global standard for business conduct data and driving positive and meaningful change through transparency.

We offer

An entrepreneurial, international, and dynamic work environment A shared mission to drive accountability and responsible behavior of companies, thus creating positive change A company that embraces diversity, because life would be boring if we were all the same!

About You

Are you looking for an opportunity to build robust, scalable data infrastructure that powers meaningful, cutting-edge machine learning projects? Do you want to work at a company where your contributions have a real, measurable impact - and you're recognized and rewarded for it?


If you're passionate about data architecture, pipelines, and enabling ethical tech development, then this is the perfect role for you. We value autonomy, giving you the space to bring innovative engineering solutions to life in an inclusive, feedback-oriented environment. Your work will directly support NLP and machine learning initiatives that drive corporate responsibility through technology.

Your Responsibilities

As our new Data Engineer, you will play a crucial role in developing, integrating, running and updating state-of-the-art Machine Learning applications within RepRisk's Machine Learning Incidents team. You will contribute to the design, implementation and operation of Data and Machine Learning products within the company as part of our global Technology division. Moreover, you will:

Develop and nurture high-load streaming applications delivering machine learning predictions Design, build, and maintain scalable and reliable ETL/ELT pipelines using state of the art tools. Automate data extraction operations through data pipelines Optimize data storage and processing for performance and cost-efficiency Collaborate cross-functionally to define data models and data contracts. Ensure data quality, observability, and compliance Contribute to documentation and internal data engineering standards Keeping up with the latest data engineering trends Participating in code reviews to maintain high standards of code quality Engage in Scrum team discussions, where your insights are highly valued

Qualifications

You Offer

A Bachelor's Degree within subjects related to computer science, STEM 3+ years of experience in Data Engineering or similar role Strong Python and SQL skills Experience with Batch (Glue / dbt) and Stream Processing (Kafka) Experience with Data Orchestration tools (Airflow, Dagster) Familiarity with version control (Git) and CI/CD Familiarity with a cloud platform (AWS preferred) Initiative and drive to push things forward Strong communication skills with a proficiency in English Experience with Data Lakehouse concepts and technologies (Databricks, Snowflake)

Additionally, the following are a plus

Experience integrating with Metadata tools such as Collibra, OpenMetadata etc., Familiarity with Great Expectations, SODA or similar frameworks Experience with Dimensional Data Modelling and Data Vault Data Modeling. Delivering workflow configurations in BPM based software such as Camunda etc., Experience working with Machine Learning teams, familiarity with ML/DL/NLP concepts

Additional Information

Please note that we will only consider candidates with a valid work permit.