Senior Data Engineer - Analytics
$170k - $200k • Remote • Remote - US
Posted 5d ago
About the job
Machinify is a leading healthcare intelligence company that provides value, transparency, and efficiency to health plan clients. Our AI-powered platform and expertise are used by over 85 health plans, representing more than 270 million lives. We are constantly innovating to improve financial outcomes and reduce healthcare costs.
As a Senior Data Engineer (Analytics), you will be responsible for transforming raw operational data into actionable insights for business leaders. This role focuses on data modeling and measurement enablement, working closely with business stakeholders to understand their needs and translate them into certified models, robust metric definitions, and user-friendly reports. You will be instrumental in unifying data from multiple platforms into a single measurement model across diverse client workflows.
Responsibilities
- Collaborate with business stakeholders to understand needs and define acceptance criteria.
- Model noisy healthcare operational data into certified dimensional models using Databricks, dbt, and SQL.
- Own and define metrics with clear, documented definitions for a governed semantic layer.
- Build and manage the visualization layer, including Power BI semantic models, dashboards, and reports.
- Implement and maintain model observability, including freshness, latency, and anomaly detection.
- Manage orchestration for built components, including dbt Cloud jobs and Airflow DAGs.
- Create and maintain documentation for designs, models, and knowledge bases.
- Automate recurring work using AI-assisted workflows and LLMs.
- Write concise and clear documentation, definitions, and reports for business consumption.
Requirements
- 6+ years of experience in analytics engineering, BI engineering, data engineering, or business analysis with production ownership.
- Expert SQL and strong dimensional modeling skills.
- Proficiency in production dbt, including models, tests, macros, exposures, documentation, and CI.
- Hands-on experience with cloud lakehouses or warehouses (Databricks and Spark SQL preferred).
- Demonstrated talent in visualization and BI semantic layers (Power BI and DAX strongly preferred).
- Fluency in stakeholder communication, translating business needs into technical requirements.
- Strong reconciliation skills to investigate data discrepancies.
- Proficiency with Git and pull-request workflows.
- Experience with Python for tasks like API calls and file parsing, with judgment to use SQL when appropriate.
- Comfort with high autonomy in a fast-paced, async, Slack-first environment.
- Strong writing skills for documentation and communication.