Key duties and responsibilities
Under the responsibility of a Lead Data Engineer, your mission will be to:
1. Build, deliver, test, maintain data artefacts such as data pipelines & services (API) to serve data distribution while following standard best practices;
2. Document data artefacts (code, diagrams, wiki-like documentation) to secure the comprehensiveness of your work;
3. Collaborate within and outside your squad by participating to workshops or rituals (dailys, sprint reviews, design sessions);
4. Support the delivery of trust-worthy data pipelines that serve both transactional and analytical needs, by implementing adequate tests and controls;
Review and coach data engineers, support them by helping them to grow.
Required experience & competencies
6+ years of experience as a data engineer, data oriented mindset;
Proven experience in development and maintenance of data pipelines, preferably in agile projects (Scrum and/or Kanban);
Proven experience with Databricks and/or Palantir Foundry is a strong plus;
Experience in (Re)insurance industry and/or Financial Services is a plus.
Technical Skills:
Strong level in Python, Pyspark and SQL, ability to develop data pipelines under various platform using good practices such as parallelization, distributing programing techniques, decisional modeling, slowly changing dimensions, change data capture management;
Good knowledge of CI/CD pipelines and Gitflows best practices;
Knowledge of REST API development;
Knowledge of reporting tools (e.g. Power BI) is a plus.
Behavioral & Management Skills:
Strong analytical thinking, rigorous mindset solution-oriented and force of proposal;
Team player, commitment, curiosity, interest to challenge;
Capacity to navigate in an international environment;
Communication, ability to speak to a wide community of stakeholders (business, data, IT).
Required Education
Bachelor's degree in computer science, software or computer engineering, applied math, physics, statistics, or a related field or equivalent experience.