Azure 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.

Requirements/Skills:

-2-4 years of experience working in a cloud data engineer role;
-Hands on experience with Azure Data Lake, Azure Data Factory, SQL Data Warehouse Azure Blob, Azure Storage Explorer;
-Good to have knowledge on Power BI in Report development, Data Modelling;
-Proficient in creating Azure Data Factory pipelines for ETL processing; copy activity, custom Azure development etc;
-Design and develop batch and real-time streaming of data loads to data warehouse systems;
-Good technical knowledge in Microsoft SQL Server;
-Experience building data ingestion pipelines for a cloud, with data consumable by business intelligence solutions (e. g. PowerBI) and/or data scientists;
-Familiarity with the Azure cloud ecosystem, specifically with data intensive components like Azure Synapse, CosmosDB, Data Factory, Databricks;
-Routine command of observability approaches for the clouds: logging, monitoring, tracing;

Education And Work Experience:

-Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics;
-2 to 4 years of professional experience with Data Management technologies and a minimum of 2 years Azure Data Factory, Azure Synapse (DWH), Azure SQL Database, -Azure Data Bricks, Spark, and Data Explorer;
-2 to 4 years of designing Big Data Pipelines supporting Data Science Use Cases;
-4+ years of experience of IT platform implementation in a highly technical and analytical role;

Responsibilities:

-Scope and execute together with team leadership. Work with the team to understand platform capabilities and how to best improve and expand those capabilities;
-Strong independence and autonomy;
-Assist in the design, development, enhancement, and maintenance of complex data pipeline products which manage business-critical operations and large-scale analytics applications;
-Support analytics, data science and/or engineering teams and understand their unique needs and challenges;
-Instill excellence into the processes, methodologies, standards, and technology choices embraced by the team;
-Embrace new concepts quickly to keep up with fast-moving data engineering technology;
-Dedicate time to continuous learning to keep the team appraised of the latest developments in the space;
-Commitment to developing technical maturity across the company;

What will you do each day?

-Create processes to import new datasets.
-Ensure data is transformed to its final form to be used by analysts and developers;
-Make sure all of our existing data import jobs run successfully;
-Use your knowledge and technical skills to find creative ways to identify and correct anomalies in our data;
-Verify that the data that was imported is correct and notify the team if you found any problems;
-Document existing databases, database warehouses and processes;
-Identify areas where improvements can be made;
-Manage multiple requests with varying priorities to ensure we meet project deadlines;
-Answer data-related questions from other members of the department;
-Brainstorm ways to provide more value to end users through our data;

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);
-Opportunity to work with Top Clients on large projects;
-Continuous learning and improvement activities;
-Dynamic, international working environment;
-Long term career development programs.