Enterprise Data Analytics Engineer

We are looking for a Data Analytics Engineer to help strengthen and scale analytics capabilities supporting participant and healthcare-related data initiatives in Boston, Massachusetts. This role is ideal for an early-career data specialist who enjoys building reliable datasets, improving reporting foundations, and partnering with analysts and business teams to turn complex information into actionable insight. You will work in a modern cloud data environment and contribute to data products that support performance measurement, operational visibility, and informed decision-making.

Responsibilities:

• Build and support data pipelines, curated datasets, and analytics-ready data structures used for reporting and performance tracking.

• Clean, join, and reshape data from multiple sources to produce dependable outputs for dashboards, KPI measurement, and deeper analysis.

• Partner with analysts, engineers, and business stakeholders to translate reporting needs into practical data models and scalable solutions.

• Investigate pipeline failures and data inconsistencies, then implement fixes that improve reliability, accuracy, and timeliness.

• Maintain clear documentation for data definitions, model logic, source mapping, and lineage to improve transparency across the analytics function.

• Create recurring and on-demand analyses that help teams monitor trends, evaluate outcomes, and support current business priorities.

• Contribute to the upkeep and optimization of analytics workflows within tools such as Databricks, Microsoft Fabric, and related cloud platforms.

• Provide data support to operational teams and assist with information requests tied to cross-functional initiatives or external-facing needs.

Qualifications:

• At least 1 year of experience in a data engineering, analytics engineering, or data analyst role with hands-on work in SQL and ETL processes.
• Practical experience with Databricks, Azure Databricks, Microsoft Fabric, or comparable modern cloud data platforms.
• Familiarity with building, maintaining, and troubleshooting data pipelines in a warehouse or lakehouse environment.
• Working knowledge of data modeling principles and an understanding of how curated datasets support reporting and business analysis.
• Ability to write clear, efficient SQL for data extraction, transformation, validation, and performance analysis.
• Experience collaborating with both technical and non-technical partners to gather requirements and deliver usable data assets.
• Exposure to tools or practices such as version control, testing, documentation, and data quality monitoring.
• Healthcare or participant-focused data experience is preferred but not required.

Compensation

$90,000.00-$110,000.00 Yearly

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