Data Engineer (Azure, Fabric, Databricks)

Collectiv is a leading boutique consulting and strategy firm specializing in Analytics, Planning, and AI. The Data Engineer is responsible for designing, implementing, and supporting modern data platforms using Microsoft Fabric and Databricks, focusing on lakehouse architecture and analytics engineering while collaborating with client stakeholders and cross-functional teams.

Responsibilities:

• Design and implement modern data platforms leveraging Microsoft Fabric (OneLake, Lakehouse, Data Factory, Power BI) and Databricks (Spark, Delta Lake, SQL Warehouses)
• Build and optimize data ingestion, transformation, and orchestration pipelines using ELT/ETL best practices
• Develop scalable lakehouse architectures that support analytics, reporting, and downstream data products
• Translate business and analytical requirements into technical designs and data models
• Develop and maintain semantic models that enable performant reporting and self-service analytics
• Partner with analytics and business teams to deliver trusted datasets and dashboards (Power BI or equivalent)
• Ensure data quality, reliability, and usability across the analytics platform
• Write, optimize, and tune SQL and Spark-based transformations for large-scale analytical workloads
• Apply version control, CI/CD concepts, and code review standards to data engineering workflows
• Ensure solutions meet quality criteria related to performance, scalability, and maintainability
• Work directly with client stakeholders to gather requirements, communicate technical concepts, and manage expectations
• Collaborate with project managers, architects, and fellow consultants to align technical delivery with project goals
• Contribute to internal documentation, reusable patterns, and knowledge sharing across Collectiv

Requirements:

• Bachelor's degree from an accredited university
• 4+ years of experience in data engineering, analytics engineering, or data platform consulting
• Hands-on experience with Microsoft Fabric and/or Databricks in production environments (experience with both strongly preferred)
• Strong SQL skills, including performance tuning and optimization
• Experience designing data models for analytics (star schemas, semantic models, lakehouse patterns)
• Experience working in cloud data platforms (Azure preferred)
• Ability to work independently in a client-facing consulting role
• Experience migrating or modernizing data platforms (e.g., legacy DW to lakehouse)
• Familiarity with Power BI dataset modeling and performance optimization
• Experience integrating data platforms with downstream applications or APIs
• Consulting experience with multiple clients or industries
• Strong written and verbal communication skills
• Relevant Azure certifications (e.g., Azure Solutions Architect, Azure Data Engineer), Fabric (DP-600, DP-700) certifications, and Databricks certifications are highly desirable