Data Engineer (Microsoft Fabric)

About RethinkFirst 

RethinkFirst is a leading behavioral health technology company working to make mental wellness, education, and support accessible and scalable. Through our suite of cloud-based platforms—including RethinkEd, RethinkCare, and RethinkBH—we serve educators, employers, and providers with tools that deliver measurable, inclusive outcomes. 

We're on a mission to make behavioral health more effective, equitable, and human.
 

About the Role 

We're seeking a highly skilled and motivated hands-on Data Engineer to design, build, and maintain our Microsoft Fabric Lakehouse as we migrate our Azure-Synapse enterprise data warehouse and analytics platform. You'll own the full lifecycle — from designing scalable pipelines and dimensional models to delivering reliable, secure data across the organization and supporting it in production.

You'll thrive here if you're fluent across Microsoft Fabric, Azure Synapse, and Databricks, comfortable using C# for API integrations, communicate clearly with both technical and business partners, and take genuine ownership of outcomes from design through production support.

What You'll Do

Data Modeling & Lakehouse / Warehouse Development

• Design, build, and maintain scalable Lakehouse and data warehouse solutions on Microsoft Fabric and Azure Synapse

• Develop, optimize, and deploy ETL/ELT pipelines and reusable framework for seamless data integration from multiple diverse sources

• Implement data quality, validation, and transformation logic across pipelines, ensuring accuracy and consistency

• Establish best practices for data engineering, including coding standards, governance, performance, and automation

• Document models, pipelines, and operational runbooks so others can support and extend the platform

• Develop and optimize dimensional/Semantic models for advanced BI and analytics

Data Integration & Operations

• Integrate diverse source systems into the enterprise data warehouse

• Ensure pipelines and Lakehouse/warehouse workloads are scalable, reliable, performant, and secure

• Tune SQL, Spark jobs, and pipeline performance for cost and reliability

• Implement monitoring, alerting, and operational practices for data workflows

• Respond to production incidents, trouble-shoot root-causes, and implement effective solutions

• Proactively identify gaps, propose improvements, and drive work to completion with minimal oversight

• Implement API integrations and services where the platform requires it

Collaboration & Delivery

• Partner with architects, analysts, product, and business stakeholders to translate requirements into Lakehouse/warehouse solutions

• Communicate progress, risks, and tradeoffs clearly to both technical and non-technical audiences

• Work within Agile/Scrum practices — planning, estimation, and demos

• Collaborate effectively across onshore and offshore teams

• Conduct and participate in Code Reviews to ensure code quality and maintainability

What You Bring

Required Qualifications

• 2-5 years of hands-on experience in data warehouse / data engineering roles

• Practical, production experience across Azure Synapse, Microsoft Fabric, and Azure Databricks

• Strong SQL plus Python and/or scripting for transformation, automation, and tooling

• Proven experience building and optimizing ETL/ELT pipelines and data models

• Experience delivering within Agile/Scrum teams

• Strong written and verbal communication skills

• Demonstrated initiative, ownership, and reliability in delivering production data solutions

Preferred Qualifications

• Experience with healthcare data systems

• Familiarity with the ABA (Applied Behavior Analysis) domain

• Experience with C# for API integrations and services

• Exposure to AI (Azure OpenAI, Claude, Cursor)

• Experience collaborating with distributed or offshore teams

Who You Are

• You take initiative — you spot issues and opportunities, then drive solutions forward

• You're accountable — you own quality, reliability, and follow-through

• You communicate clearly — you can explain technical work to any audience

Benefits: 

• Generous