Data Engineer

Why we’re different:

At Capgemini, we help organizations across the world become more agile, more competitive and more successful. Smart, tailored, often ground-breaking technical solutions to complex problems are the norm. But so, too, is a culture that’s as collaborative as it is forward thinking. Working closely with each other, and with our clients, we get under the skin of businesses and to the heart of their goals. You will too.


Capgemini is proud to represent nearly 130 nationalities and its cultural diversity. Our holistic definition of diversity extends beyond gender, gender identity, sexual orientation, disability, ethnicity, race, age and religion. Capgemini views diversity as everything that makes us who we are as an organization, including our social background, our experiences in life and work, our communication styles and even our personality. These dimensions contribute to the type of diversity we value the most: diversity of thought.

Technical skills:

-At least 5 years of relevant work experience in data engineering & data operations;
-Hands-on experience with handling different file types (CSV, XLSX, JSON, TXT) in Python;
-Proficient in using the Django framework for data modeling and SQL transformations (DDL generation of data sources, script generation & logging);
-Good knowledge of the AWS data stack & services (such as S3, Lambda & RDS);
-Familiarity with planning, implementing and correctly executing the scheduling of the ETL flows to ensure they fit in the overall data platform design;
-Familiarity with Confluence & Jira;
-Ability to troubleshoot and debug data pipeline issues;
-Experience with SQL (Postgres) is an advantage;

Management skills:

-Strong analytical and communication skills;
-Critical, accurate and correct;
-Familiarity with acting as part of an agile team and participating in daily stand-ups;
-Strong collaboration skills;
-Can work in a structured way and is able to maintain the documentation on Confluence;
-Attach great importance to privacy & ethics;
-Able to communicate fluently in English ;

This is an excellent opportunity to join a fast-paced, dynamic team and make a significant impact on the success of our organization. If you are passionate about data engineering and have a track record of success in building data pipelines on AWS using the Django framework, we encourage you to apply.

The main objective of the data engineer is to build the framework that supports the entire lifecycle of data-driven products through data pipelines. This means you develop the ETL flows to efficiently retrieve the necessary data from various sources, transform data according to the pre-defined business logic and eventually integrate data into the data platform. Data quality and robustness of the ETL processes are of great importance here.

Next to that, you will also participate in the further development of the data platform, which provides data & insights to various business stakeholders.

Benefits:

-Flexible working environment within a dynamic team;
-Access to various training programs and platforms (e.g.: content provided by Pluralsight, Harvard and Coursera);
-Attractive benefits package (meal tickets, medical services, gym discounts);
-ESPP(employee stock purchase program);
-Opportunity to work with Top Clients on large projects;
-Continuous learning and improvement activities;
-Dynamic, international working environment;
-Long term career development programs;