[High Salary] Technical Architect-Azure Data Engineering

Job Description

Atos is a global leader in digital transformation.European number one in Cloud, Cybersecurity and High-Performance Computing, the Group provides end-to-end Orchestrated Hybrid Cloud, Big Data, Business Applications and Digital Workplace solutions. The Group is the Worldwide Information Technology Partner for the Olympic & Paralympic Games and operates under the brands Atos, Atos Syntel, and Unify. Atos is a SE (Societas Europaea), listed on the CAC40 Paris stock index.

The purpose of Atos is to help design the future of the information space. Its expertise and services support the development of knowledge, education and research in a multicultural approach and contribute to the development of scientific and technological excellence. Across the world, the Group enables its customers and employees, and members of societies at large to live, work and develop sustainably, in a safe and secure information space

Role Overview

As a Technical Architect specializing in Azure Data Engineering, you will play a pivotal role in designing and implementing scalable, high-performance data solutions on the Azure platform. You will collaborate with cross-functional teams to architect solutions that address complex business challenges, ensuring alignment with Atos vision for data-driven transformation.

Responsibilities

- Solution Design Develop end-to-end technical architectures for data engineering projects, leveraging Azure services such as Azure Data Factory, Azure Databricks, Synapse Analytics, and ADLS Gen2.
- Leadership Lead and mentor a team of data engineers, fostering a culture of innovation and excellence.
- Collaboration Work closely with business stakeholders, data scientists, and developers to translate business requirements into technical solutions.
- Optimization Ensure the performance, scalability, and security of data pipelines and architectures.
- Innovation Stay updated on emerging Azure technologies and integrate them into Atos offerings.
- Documentation Create comprehensive technical documentation and present solutions to clients and internal teams.

Key Technical Skills & Responsibilities

- 15+ years of experience in data architecture, data engineering, and cloud platform modernization.
- Minimum 23 Azure data implementations involving on-prem to cloud migration and end-to-end solution delivery.
- Expertise in Azure Data Factory, Azure Databricks, Azure Synapse Analytics, ADLS Gen2, Azure SQL DB, and Blob Storage.
- Batch processing solutions that use Data Factory and Azure Databricks
- Proficiency in Python, SQL, or Scala for scalable transformation and data engineering.
- Strong command of Apache Spark (PySpark or Spark SQL) and Delta Lake for big data pipelines.
- Must - Architectural experience with Microsoft Fabric, including Fabric Workspaces, Lakehouses, Real-Time Analytics, DirectLake, and semantic layer generation.
- Non-relational cloud data stores
- Solutions using Cosmos DB,Cosmos DB API
- Real-time processing by using Stream Analytics and Azure Databricks
- Must have experience of working with streaming data sources and Kafka (preferred).
- Deep understanding of data modeling, schema design, and modern data warehousing techniques.
- Hands-on knowledge of CI/CD, version control with Git, and IaC with Terraform/ARM.
- Security for data policies and standards
- Data encryption for data at rest and in transit
- Data auditing and data masking
- Data privacy and data classification
- Data retention policy
- Experience in pre-sales, solutioning, RFPs, and technical proposal writing, with ability to translate business needs into technical solutions.
- Optimal data ingestion method for a batch processing solution where processing should take place, such as at the source, at the destination, or in transit

Eligibility Criteria

- Proven experience in Azure Data Engineering, with expertise in services like Azure Data Factory, Databricks, Synapse Analytics, and ADLS Gen2 using Azure Fabric.
- Strong programming skills in Python, SQL, and Spark.
- Deep understanding of data modeling, ETL processes, and data pipeline optimization.
- Excellent problem-solving skills and the ability to work in a fast-paced environment.
- Strong communication and leadership skills.
- Relevant certifications in Azure (e.g., Azure Solutions Architect, Azure Data Engineer Associate) are a plus.