Data Engineer (Azure, Fabric, Databricks)

Role Overview

The Data Engineer is responsible for designing, implementing, and supporting modern data platforms using Microsoft Fabric and Databricks , with a strong emphasis on lakehouse architecture, analytics engineering, and semantic modeling. This role is client-facing and requires translating business requirements into scalable technical solutions while adhering to data engineering best practices.

You will collaborate with client stakeholders, Collectiv consultants, and cross-functional teams to deliver data platforms that support reporting, advanced analytics, and self-service BI.

Key Responsibilities

Client Delivery & Solution Design

- 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

Analytics & BI Enablement

- 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

Engineering Best Practices

- 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

Consulting & Collaboration

- 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

Required Qualifications

- 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

Preferred Qualifications

- 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

What Success Looks Like in This Role

- Clients trust you as a technical advisor for their data platform decisions

- Delivered solutions are scalable, well-documented, and aligned to best practices

- Business users are enabled through reliable data models and analytics-ready datasets

- You actively contribute to Collectiv ’s data platform standards and consulting excellence

Join Collectiv for a rewarding career in a fully remote work environment with quarterly in person team experiences and a competitive compensation. We provide a clear growth trajectory with professional development opportunities and a top-shelf benefits package. Enjoy unlimited time off and 100%