Senior Member of Technical Staff

Role Summary

athenahealth is looking for aDeveloper-Analystto join thePatient Directoryteam within the Platform organization. Patient Directory helps healthcare organizations identify and match patient data across athenahealth's network and related data sources.

This role sits at the intersection of data analysis and engineering. You will spend most of your time analyzing large-scale datasets, identifying patterns, and delivering insights that support product and platform decisions. You will also contribute to backend systems, scripts, pipelines, and workflows that support those analytical needs. The role is well suited for someone who is comfortable working across data and code, and who can translate technical findings into clear, practical recommendations.

Team Summary

The Patient Directory team works on data and platform capabilities that support patient identity matching and related workflows. The team collaborates across product, engineering, and data functions to improve data quality, support analytical insight, and strengthen the systems that enable reliable patient matching at scale.

Team members work with large datasets, data models, and distributed systems to help surface patterns, improve workflows, and support product decisions. The team values curiosity, ownership, collaboration, and the ability to move between analysis and implementation as needed.

Essential Job Responsibilities

• Analyze large-scale datasets, including patient records, to identify patterns, anomalies, and opportunities to improve matching algorithms and data quality.

• Write complex SQL and NoSQL queries to extract, transform, and interpret data across relational and non-relational data stores.

• Use Snowflake as a primary data warehouse for querying, modeling, and analysis.

• Build and maintain dashboards and reports for team members, leadership, and product stakeholders.

• Translate analytical findings into clear, actionable recommendations for engineering and product teams.

• Collaborate with data engineers and platform developers to understand data lineage, pipeline behavior, and schema design.

• Identify data quality issues and help define and implement remediation strategies.

• Support ad hoc analytical requests from product, clinical, and business stakeholders.

• Work with existing data, scripts, and workflows and extend them as analytical needs evolve.

• Build new data workflows or lightweight backend services when needed to support analysis or reporting.

• Write clean, maintainable code that follows team standards for testing, documentation, and code review.

• Contribute to API and microservices work as needed, especially where data access patterns are involved.

• Partner with product managers, engineers, and other teams to define analytical requirements and success metrics.

• Present findings and dashboards to technical and non-technical stakeholders in a clear and accessible way.

• Share learnings across the broader engineering and data organization.

• Use AI-assisted tools to help write and debug code, optimize queries, accelerate analysis, and improve reporting workflows while applying human judgment to validate outcomes.

Additional Job Responsibilities

• Support the team in improving data quality, workflow reliability, and analytical visibility.

• Contribute to planning and execution of analytical and technical work in an Agile environment.

• Participate in discussions that improve data access, reporting, and operational decision-making.

• Apply sound judgment when working through ambiguous problems across data and engineering contexts.

• Take ownership of deliverables end to end and work collaboratively across functions.

Expected Education & Experience

• Bachelor's degree in Computer Science, Information Systems, Statistics, or an equivalent field.

• 4 to 8 years of experience in a developer, analyst, or hybrid role.

• Strong proficiency in SQL, including joins, window functions, aggregations, and query optimization.

• Hands-on experience with Snowflake or a comparable cloud data warehouse.

• Experience with NoSQL databases such as MongoDB, DynamoDB, Cassandra, or similar.

• Proficiency in Power BI and/or Tableau for dashboard development and reporting.

• Experience using Python or a similar scripting language for data analysis.

• Familiarity with ETL/ELT pipelines and data modeling concepts.

• Experience working in an Agile environment.

• Strong analytical mindset with the ability to ask the right questions of data and identify meaningful patterns.

• Ability to communicate complex findings clearly to both technical and non-technical audiences.

• Comfort working in ambiguity across both data and engineering contexts.

• Strong ownership of work from analysis through execution.

• Collaborative approach and ability to work effectively across functions.

• Java or Spring Boot development experience.

• Experience with distributed data processing frameworks such as Spark or Kafka.

• Exposure to AWS services such as ECS, EKS, and S3.

• Experience with healthcare data or patient data standards such as FHIR and HL7.

• Knowledge of data quality frameworks and matching or deduplication algorithms.

• Demonstrated use of AI-assisted development or analysis tools in a professional setting to improve throughput or quality.