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Data Engineer
2 weeks ago
Description :
Dentsu & DGS :
Dentsu is a global leader in integrated communications, media, and digital services, operating across 145 countries with over 65,000 professionals. Dentsu Global Services (DGS) is the enterprise technology and innovation hub of Dentsu, driving the organizations AI-first transformation through scalable, data-driven, and cloud-native solutions. DGS specializes in digital platforms, data engineering, analytics, product engineering, and automation, enabling global clients to harness the power of connected intelligence.
Role Overview :
As a Data Engineer - Solutions & Onboarding (MS Fabric), you will be responsible for architecting, building, and maintaining data solutions that enable seamless ingestion, transformation, and delivery of data across the Dentsu ecosystem. You will work on the Microsoft Fabric platform to develop scalable and secure data pipelines, optimize processing performance, and ensure high data quality and availability. This role demands deep technical expertise, a data-centric mindset, and the ability to collaborate with cross-functional teams to drive data-driven decision-making.
Key Responsibilities :
Data Pipeline Design & Development :
- Architect and develop robust, end-to-end data pipelines leveraging Microsoft Fabrics Data Lakehouse architecture (Bronze/Silver/Gold layers).
Data Ingestion & Integration :
- Implement efficient ingestion mechanisms for structured and unstructured data from multiple sources - including on-premises systems, cloud platforms, APIs, and streaming data sources.
Real-time & Batch Processing :
- Develop scalable real-time (streaming) and batch data processing solutions using Spark Notebooks, Dataflows, and Microsoft Fabric Pipelines.
Optimization & Performance Tuning :
- Monitor and fine-tune data pipelines for throughput, latency, cost-efficiency, and reliability using Fabric-native monitoring tools and Azure best practices.
Data Quality & Governance :
- Enforce high data standards through validation, lineage tracking, and metadata management, ensuring compliance with organizational governance policies.
Collaboration & Solution Delivery :
- Work closely with data architects, analysts, BI developers, and platform engineers to deliver consistent, validated, and high-performing data sets for analytics and reporting.
Automation & Scalability :
- Develop automation frameworks for data onboarding, versioning, and deployment processes to streamline environment setup and reduce manual interventions.
Qualifications & Technical Expertise :
Education :
- Bachelors or Masters degree in Computer Science, Information Technology, or related engineering field.
Experience :
- Minimum 5 years of experience in data engineering, with a focus on cloud-based architectures and data integration.
Core Skills :
- Proficiency in Microsoft Fabric, Azure Synapse, Azure Data Factory, ADLS Gen2, and Databricks (preferred).
- Strong expertise in SQL, Python, and PySpark for data transformation and orchestration.
- Experience with ETL/ELT pipelines using modern tools such as Alteryx, ADF, or Fabric Pipelines.
- Solid understanding of data modeling, data lakehouse architectures, and data warehousing principles.
- Hands-on knowledge of real-time data streaming frameworks (e.g., Kafka, Event Hubs) and message-driven systems.
- Familiarity with CI/CD for data pipelines, version control (Git), and infrastructure as code tools.
- Awareness of data governance, security, and compliance frameworks within cloud environments.