Arbetsbeskrivning

Job Description:

Our client is seeking a skilled Senior Data Engineer to establish and enhance the core data infrastructure supporting performance evaluation and CMP (Customer Meeting Point) insights. This role focuses on designing and maintaining scalable data platforms that unify and streamline data from multiple operational sources.

The selected candidate will be responsible for building robust data pipelines that ingest, transform, and organize complex datasets into a centralized environment. These datasets include sales, cost-to-serve, customer experience insights, brand metrics, and range-related information. The objective is to eliminate fragmented and inconsistent data by implementing reliable, automated, and high-quality data solutions.

The role also involves developing scalable data models and frameworks that ensure accuracy, consistency, and availability of data across systems. By introducing automated validation mechanisms and performance optimizations, the engineer will enable faster reporting, improved decision-making, and a seamless omnichannel experience.

This position requires active participation throughout the full data engineering lifecycle, from initial concept and architecture design to development, deployment, and operational support. The candidate will collaborate closely with both technical and non-technical stakeholders, acting as a key contributor to building a strong CMP data foundation.

Key Responsibilities:

• Architect, develop, and maintain end-to-end data pipelines for batch and streaming data processing
• Consolidate and integrate diverse datasets into a unified and scalable data platform
• Design efficient data models aligned with lakehouse architecture principles
• Implement automated data validation, monitoring, and quality assurance mechanisms
• Optimize performance and ensure reliability of data pipelines in production environments
• Contribute to solution design, including high-level and low-level architecture and technical specifications
• Manage data ingestion, transformation, and serving layers using modern data engineering practices
• Work extensively with Databricks (Apache Spark, Delta Lake) for data processing and orchestration
• Utilize Microsoft Azure services, including Data Lake Storage, for scalable data solutions
• Apply DevOps practices such as version control, CI/CD pipelines, automated testing, and infrastructure as code
• Collaborate with stakeholders to translate business requirements into technical data solutions
• Support deployment, monitoring, troubleshooting, and continuous improvement of data platforms

Total Years of Experience:

Senior-level experience required

Education:

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Information Technology, or a related field

Required Skills:

• Strong expertise in end-to-end data engineering
• Hands-on experience with Databricks, Apache Spark, and Delta Lake
• In-depth knowledge of Microsoft Azure data platform services (e.g., Azure Data Lake Storage)
• Proficiency in data modeling and lakehouse architecture
• Experience in data quality, validation, and reliability engineering
• Solid understanding of DevOps practices, including CI/CD and infrastructure as code
• Strong problem-solving and analytical capabilities
• Effective communication and stakeholder collaboration skills

Languages:

• English – Proficient

Job Mode:

Hybrid (25% Remote – Onsite presence required 3 days/week) | Full-time (40 hours per week)

Application Method: Interested candidates can apply by sending their profile to [email protected]