Data Engineer (Lakehouse)

Key Responsibilities

• Design, develop, and maintain Lakehouse architectures using Medallion (Bronze, Silver, Gold) patterns
• Build and optimize data pipelines using Databricks (Spark, Delta Lake) and Microsoft Fabric
• Ingest, transform, and curate structured and semi‑structured data from enterprise systems
• Implement performance tuning techniques for Spark jobs, Delta tables, and Fabric workloads
• Ensure data quality, reliability, and lineage across analytical layers
• Collaborate with analytics, reporting, and business teams to deliver trusted datasets
• Implement best practices for data partitioning, indexing, and storage optimization
• Support CI/CD, monitoring, and operationalization of data pipelines
• Adhere to Fluor’s Quality, and Information Security standards
• Document technical designs, data models, and operational procedures
• Provide technical guidance and support to junior engineers as required

Basic Job Requirements

• Bachelor’s degree in Computer Science, Information Systems, Engineering, or related field
• 5+ years of experience in data engineering or data platform development
• Minimum 5 years relevant data engineering experience in enterprise environments
• Strong hands‑on experience with Databricks (Apache Spark, Delta Lake)
• Experience with Microsoft Fabric (Lakehouse, Data Pipelines, OneLake)
• Proven expertise in Medallion Architecture implementation
• Strong SQL and data modeling skills
• Experience with performance tuning of large‑scale data pipelines

Other Job Requirements

Preferred Qualifications

• Experience supporting EPC, engineering, construction, or industrial projects
• Exposure to Azure data services (ADLS, Synapse, Data Factory)
• Knowledge of Power BI semantic models and analytics consumption patterns
• Experience with DevOps / CI‑CD for data platforms
• Familiarity with data governance, security, and compliance practices
  • Azure / Databricks certifications preferred