Senior Data Engineer

Description

We are looking for a Senior Data Engineer to join a growing data team supporting an innovative healthcare-focused program in Boston, Massachusetts. In this role, you will design and optimize data solutions that transform complex patient, medical, financial, and marketing information into reliable assets for analytics and leadership reporting. This position offers the opportunity to work remotely while partnering closely with technical and business stakeholders to build scalable data pipelines in a modern Azure environment.

Responsibilities:
Design, build, and maintain robust data pipelines that ingest, transform, and organize information from multiple sources for downstream analytics use.
Develop scalable data engineering solutions using Databricks, Azure Data Factory, SQL, and Python within a cloud-based architecture.
Integrate and prepare diverse datasets, including patient-related, clinical, financial, and marketing data, to support reporting and business insights.
Collaborate with business intelligence partners to deliver clean, dependable datasets that power dashboards, reporting, and decision-making for leadership teams.
Write efficient SQL and transformation logic to solve complex data challenges and improve the performance and reliability of existing workflows.
Partner with architects and cross-functional stakeholders to define data models, engineering standards, and best practices across the platform.
Monitor pipeline health, troubleshoot data issues, and implement improvements that strengthen data quality, accuracy, and operational stability.
Contribute as a senior member of a small engineering team by sharing technical guidance, communicating clearly, and supporting long-term platform growth.

Requirements

5+ years of hands-on experience in data engineering or a closely related field.
Strong hands-on expertise with SQL, including advanced query development and performance optimization.
Experience building ETL/ELT workflows for large and varied datasets in production environments.
Proficiency with Azure Databricks and Azure Data Factory for cloud-based data processing and orchestration.
Working knowledge of Python for data engineering, automation, or pipeline development.
Ability to work with multiple data domains, such as healthcare, financial, marketing, or other regulated and high-volume data types.
Strong communication skills and the ability to collaborate effectively with technical teams, analytics partners, and business stakeholders.

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