Data Analyst

OCTAGOS HEALTH, INC.•Houston, TX

About The Position

We are looking for a Data Analyst to join our team and turn complex healthcare data into actionable insights that drive clinical quality, operational efficiency, and business growth. You will work across our cardiac remote monitoring platform–spanning transmission data, clinic operations, revenue analytics, and patient outcomes–to deliver reporting, dashboards, and data-driven recommendations. This role sits at the intersection of healthcare domain knowledge and data engineering and is critical to maintaining clinical integrity while scaling our technology.

Requirements

SQLproficiency:Strong T-SQL skills including CTEs, window functions, stored procedures, and query optimization in SQL Server.
Data structures and ER modeling:Solid understanding of data structures (arrays, hash maps, trees, graphs) and the ability to design and interpret Entity-Relationship models to map complex domain relationships such as Clinic → Patient → Device → Transmission hierarchies.
Python for data manipulation:Proficiencywith Python data libraries (Pandas, NumPy,PySpark) for in-memory data transformation, cleansing, aggregation, and exploratory analysis on large datasets.
Performance optimization:Experience with query tuning, indexing strategies, partitioning, and aggregation approaches for large-volume datasets (millions of rows), including understanding execution plans, batch processing patterns, and incremental load strategies.
Data visualization:Hands-on experience with Power BI (report authoring, DAX measures, data modeling) or equivalent tools.
Statistical knowledge:Solid grasp of statistical methods including hypothesis testing, regression analysis, and forecasting techniques.
Spreadsheetproficiency:Advanced Microsoft Excel skills for ad-hoc data manipulation and analysis.
Database knowledge:Familiarity with relational database design, stored procedures, views, indexing strategies, and ETL concepts. Working knowledge of MySQL in addition to SQL Server.
NoSQL and document databases:Experience with NoSQL databases (e.g., MongoDB, Cosmos DB, DynamoDB) for handling flexible schemas, high-throughput reads, and document-oriented data models.
Unstructured and semi-structured data:Ability to ingest, parse, and transform unstructured and semi-structured data formats including CSV, JSON, XML, Parquet, and delimited flat files-extracting meaningful structure for analysis and reporting pipelines.
Azure cloud platform:Working knowledge of Azure cloud services including Azure SQL Database, Azure Data Factory, Blob Storage, Application Insights, Log Analytics,and Azure Functions-with the ability to navigate the Azure Portal,monitorresources, and support cloud-hosted data pipelines.
Analytical thinking:Ability to break down complex healthcare data problems,identifyroot causes, and propose actionable solutions.
Communication:Strong verbal and written skills to clearly present technical findings to both technical teams and non-technical clinical stakeholders.
Attention to detail:Meticulous approach to ensuring data accuracy and report reliability-critical in a healthcare/HIPAAand FedRAMPregulated environment.
Business acumen:Understanding ofhealthcare operations, SaaS metrics, or cardiology workflows is a strong plus.
Collaboration:Ability to work effectively with cross-functional teams including engineering, product, clinical operations, and sales.
AI-assisted development:ExperienceleveragingAI coding assistants and tools (e.g., GitHub Copilot, Claude, ChatGPT) to accelerate query writing, data analysis,issuetroubleshootingand workflow automation.
Issue tracking:Proficiencywith JIRA for logging, tracking, and troubleshooting data issues, managing sprint tasks, and collaborating with engineering on bug resolution.

Nice To Haves

Familiarity with .NET/C# APIs or Angular front-end development for understanding data flow end-to-end.
Exposure to healthcare data standards, HIPAA compliance, or cardiac device monitoring workflows.
Experience with Python or R for statistical analysis or machine learning.
Knowledge of AI/ML concepts and their application to healthcare automation.

Responsibilities

Build andmaintainPower BI dashboards and reports using our embedded analytics stack (Power BI Embedded, SQL Server, Azure), covering transmission volume, revenue potential, clinic performance, and operational KPIs.
Write andoptimizeT-SQL queries and stored procedures against our production and reporting databases (SQL Server), adhering toOctagosschemastandards.
Design and maintain ETL pipelines and analytics stored proceduresthat feed Power BI datasets, ensuring data accuracy and freshness.
Collect, clean, and analyze complex datasets from multiple sources including device transmissions, clinic workflows, billing records, and patient demographics.
Perform descriptive, diagnostic, and predictive analytics toidentifytrends in transmission processing times, clinicutilization, alert patterns, and revenue opportunities.
Translate complex findings into clear, visually compelling dashboards and reports for both clinical and business stakeholders, including clinic managers, executives, and the product team.
Partner with engineering, product, and clinical operations teams to define data requirements,validatebusiness logic, and ensure analytics align with platform capabilities.
Support database management tasks includingmaintainingdata systems, writing scripts for data collection and processing, andassistingwith schema documentation.
Assistin the development of AI and machine learning models to automate transmission review processes and enhance clinical decision support.
Monitor data quality and integrity across the platform, proactivelyidentifyingand resolving discrepancies between production data and reporting outputs.
Track, document, and troubleshoot data issues and bugs using JIRA, collaborating with engineering to prioritize fixes andvalidateresolutions through the full issue lifecycle.