Data Engineer Databricks

Short company description

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.

Requirements

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible.
Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.

YOUR PROFILE
• Strong experience in data engineering, with at least 1 year of hands-on Databricks expertise.
• Strong experience in Python for automation and data transformation.
• Experience working with at least one major cloud platform (AWS, Azure, or GCP).
• Strong communication skills and strong English language skills.
• Nice to have:
• Solid understanding of SQL with experience in query optimization and data modeling.
• Familiarity with DevOps methodologies, CI/CD pipelines, and Infrastructure as Code (Terraform, Bicep).
• Experience with real-time data streaming technologies such as Kafka or Spark Streaming.
• Knowledge of cloud storage solutions like Data Lake, Snowflake, or Synapse.
• Hands-on experience with PySpark for distributed data processing.
• Relevant certifications such as Databricks Certified Data Engineer Associate or cloud-based data certifications.

Responsibilities

• Automate deployments using CI/CD and infrastructure as code practices
• Design and implement data processing solutions using Databricks for large-scale and diverse datasets.
• Design, build, and enhance data pipelines with Python and cloud-native tools.
• Work closely with solution architects to define and uphold best practices in data engineering.
• Ensure data consistency, security, and scalability within cloud-based environments.

Other info

WHAT YOU''LL LOVE ABOUT WORKING HERE:

• Flexible and dynamic work environment involving teams spread across different global locations;
• Communities with shared interests and identities, all working together to advance diversity, equity and inclusion within the workplace and society;
• Do you want to learn more? You will have access to various training programs and platforms (e.g.: content provided by Pluralsight, Harvard and Coursera);
• Attractive benefits package (meal tickets, medical services, Benefit online, Employee Share Option Plan).

Capgemini is an equal opportunity employer. We promote equality and dignity in all aspects of recruitment and employment, and all offers of employment and promotions are made on the basis of performance, competence and ability.

Benefits

• Medical subscription
• Life insurance
• Trainings
• Courses
• Bookster subscription
• Choose your benefits within a maximum budget
• Laptop
• Meal vouchers