Data Architect; Data Platform

Job Title:

Data Architect (Data Platform)

As a Data Architect for healthcare applications, you are responsible for innovating, designing and managing scalable, secure, and interoperable data systems that support clinical, operational, and financial workflows. This role focuses on structuring complex healthcare data from electronic health records (EHRs) to healthcare financial data into cohesive architectures that enable accurate reporting, analytics, and patient care insights. You will ensure compliance with healthcare regulations such as HIPAA, implement industry standards like HL7 and FHIR for seamless data exchange, and establish strong data governance, quality, and security practices such as HITRUST.

By aligning data strategy with organizational goals, this role plays a critical part in improving data accessibility, reliability, and ultimately patient outcomes.

You need to be fluent in conceptual, logical, and physical data modeling, including understanding normalization vs. denormalization, dimensional modeling (star/snowflake schemas), and designing for scalability and performance.

Deep knowledge of both relational and non-relational systems is critical, including familiarity with data lakes, lake houses, and distributed storage systems/warehouses such as S3, Delta Lake, and Big Query.

Design pipelines that move and transform data reliably. Experience with ETL/ELT tools (DBT), streaming systems (Kafka, Kinesis), and orchestration frameworks (Airflow, etc.) plus understanding batch vs. real‑time tradeoffs is required.

Knowledge of indexing strategies, partitioning, query tuning, and workload management. Ability to architect for scale, resiliency, and business continuity.

• Define what the future data architecture should look like
• Determine how and where to reduce technical debt
• Identify how to enable analytics insights, incorporate AI, and drive self‑service

• Define and evolve data architectures that support AI/ML workloads, including curated training datasets, feature stores, and scalable pipelines for batch and real‑time inference
• Define and evolve data architectures that leverage AI to drive greater operational efficiency, reduce system complexity, and accelerate the ingestion and processing of healthcare data across platforms
• Design scalable pipelines and platforms (e.g., lakehouse, streaming, feature stores) that enable faster data availability for AI‑driven insights and real‑time decision support

• 12+ years of software engineering experience, including hands‑on technical experience building, maintaining and scaling data systems.
• 5+ years of experience as a tech lead who successfully converts business/product requirements into well‑architected designs.
• Extensive experience building and scaling large data pipelines, including real‑time processing and/or 100+ GB transformations in Java, Python, DBT, and SQL.
• Extensive experience driving large business outcomes by leveraging a combination of existing and new technologies.
• Deep knowledge of common data technology stacks such as GCP Big Query, Snowflake, Databricks, DBT, and Datalake architecture on AWS S3 or GCP Cloud storage.
• Deep knowledge of cloud platforms such as AWS, GCP, or Azure, and cloud‑native API solutions.
• Deep knowledge of data modeling and data governance control.
• Strong RESTful API design principles, microservices architecture, distributed asynchronous systems, and good design patterns.
• Strong knowledge with CI/CD pipelines (Circle
  
  CI, Git Hub Action), containerization (Docker, Kubernetes), version control (Git), infrastructure as code (Pulumi, Terraform), relational and No
  
  SQL databases, caching mechanisms (Redis, Memcached), and performance optimization techniques.
• Strong leadership and communication skills, with the ability to influence cross‑functional teams and communicate complex technical details to upper management and non‑technical stakeholders.
• Proven problem‑solving ability with a focus on delivering solutions.
• Positive attitude: maintaining a constructive approach to work…