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Role Description

We are looking for a skilled Microsoft Fabric Data Engineer to design, build, and optimize enterprise-scale data solutions that enable data-driven decision-making. In this role, you will:

• Develop scalable data pipelines.
• Implement Lakehouse architectures.
• Integrate diverse data sources across cloud platforms.
• Work closely with IT, analytics, and business teams to translate complex requirements into robust data solutions.
• Mentor junior engineers while delivering high-quality, reliable data services.

The environment is collaborative, fast-paced, and focused on modern data engineering practices, including automation, real-time processing, and advanced analytics. This is a remote role with milestone-based travel requirements.

Accountabilities:

• Design, build, and maintain distributed, scalable data pipelines using Microsoft Fabric and Apache Spark to process structured and unstructured data.
• Integrate data from multiple internal and external systems, ensuring consistency, reliability, and proper lineage.
• Optimize ETL/ELT workloads to improve throughput, cost efficiency, and performance of large-scale analytics environments.
• Implement and enforce data quality, metadata management, governance, and compliance standards.
• Collaborate with data scientists, analysts, architects, and business stakeholders to deliver insights and integrate analytical models.
• Document pipeline architectures, workflows, schemas, and operational processes, while troubleshooting and ensuring enterprise-grade reliability.
• Explore emerging technologies to enhance data engineering practices, including Lakehouse architecture, real-time processing, and automation.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Systems, or a related field.
• 7+ years of experience in data engineering, data architecture, or large-scale data platform development.
• Strong expertise in Apache Spark for batch and streaming processing.
• Hands-on experience with Microsoft Fabric, Data Factory, pipelines, and Lakehouse implementations.
• Advanced proficiency in SQL, Python, and/or Scala.
• Experience with cloud platforms such as Azure, AWS, or GCP.
• Solid understanding of distributed systems, lakehouse architecture, and data modeling.
• Proven ability to design and optimize complex ETL/ELT pipelines.
• Strong communication, leadership, and mentoring skills.

Requirements

• Preferred: Certifications in Azure Data Engineering, Apache Spark, or Microsoft Fabric.
• Experience with real-time streaming technologies (Kafka, Azure Event Hubs).
• DevOps practices including CI/CD and Infrastructure as Code.
• Knowledge of Power BI or Tableau.

Benefits

• Competitive salary and performance-based incentives.
• Flexible remote work with milestone-based travel opportunities.
• Comprehensive healthcare and retirement plans.
• Opportunities for professional development and skill growth.
• Collaborative and innovative technology environment.
• Access to cutting-edge data engineering tools and cloud technologies.