Sr. Cloud Data Architect

Overview

Who We Are

Ready to create a healthier world? We are ready for you! Personify Health is on a mission to simplify and personalize the health experience to improve health and reduce costs for companies and their people. At Personify Health, we believe in offering total rewards, flexible opportunities, and a diverse inclusive community, where every voice matters. Together, we’re shaping a healthier, more engaged future.

 

Responsibilities

The Senior Cloud Data Architect plays a critical role in delivering strategic and operational data solutions by designing and optimizing scalable cloud-based data architectures. This role focuses on supporting complex client and prospect needs—particularly in healthcare and TPA environments—through proactive problem-solving and cross-functional collaboration.

 

You will develop and maintain robust data pipelines, models, and systems across cloud platforms, ensuring performance, reliability, and compliance. You’ll work closely with account management, ETL, data warehouse, business intelligence, and reporting teams to deliver high-impact data solutions. As a subject matter expert, you’ll mentor Data Engineers across the platform, guiding them in data modeling, troubleshooting, and best practices. You’ll also contribute to organizational efficiency by investigating new technologies and proposing enhancements to the tech stack

 

What You'll Do

 

• Design, build, and maintain scalable ETL/ELT pipelines using AWS, Airflow, and other technologies to ingest and transform healthcare and TPA data, including claims, provider, and eligibility sources.
• Develop and operate resilient data architectures and workflows (Airflow, CloudWatch, ECS, DAGs) with strong CI/CD, observability, and governance.
• Build data applications and processes using Python, SQL, and Django; manage and query data in PostgreSQL, Oracle, and cloud-native databases.
• Examine, extract, cleanse, and load data while implementing quality assurance rules and tools to ensure consistent and accurate data.
• Work with healthcare-specific data processes such as EDI file transfers, claims adjudication, audits, eligibility verification, and reporting workflows.
• Collaborate with cross-functional teams (Data Analysts, Data Scientists, Product, Reporting, Account Management) to define requirements and deliver data-driven solutions.
• Ensure data quality, integrity, and security through automated validation, auditing, and monitoring, with compliance to HIPAA and CMS regulations.
• Monitor, maintain, and tune pipeline performance; proactively troubleshoot and resolve complex data flow and system issues.
• Provide technical mentorship to Data Engineers, sharing expertise in data modeling, pipeline development, and troubleshooting practices.
• Research and propose improvements to the tech stack and data engineering processes.
• Participate in sprint planning, refinement, and estimation to support implementation awareness and delivery.

 

Qualifications

What You Bring to Our Mission

• At least one AWS certification (e.g., AWS Certified Data Analytics – Specialty, Big Data – Specialty, Developer – Associate).
• Deep proficiency in AWS services including S3, Glue, EMR, EC2, MWAA, Lambda, Kinesis, ECS, and experience with Infrastructure as Code tools like Terraform.
• 10+ years in data engineering or analytics engineering, with a strong focus on cloud-native architectures. Proven experience designing and operating scalable data platforms in AWS.
• 5+ years in healthcare, insurance, or claims processing, including 5+ years working with EDI transactions (834, 835, 837, 2222, 2223, 999) and familiarity with HIPAA and CMS compliance.
• Deep understanding of relational and non-relational data models, including star/snowflake schemas and dimensional modeling. Skilled in PostgreSQL, Oracle, AWS RDS, Snowflake, and Redshift. Ability to mentor others in data modeling best practices.
• Expert-level proficiency in SQL (including pivots, window functions, and complex date calculations) and Python for data processing, transformation, and application development.
• Hands-on experience with orchestration tools like Airflow, containerization with Docker, and CI/CD pipelines. Strong bias for automation and continuous improvement.
• Proficient in consuming and transforming REST APIs and JSON data into relational models. Skilled in building robust data ingestion and transformation pipelines.
• Experience with JIRA, BitBucket Git, BitBucket Pipelines, and collaboration with cross-functional teams including Data Analysts, Data Scientists, Product, and Account Management.
• Proficient in Excel and BI tools such as