Principal Data Architect

Convey Health Solutions•Fort Lauderdale, FL

23h

About The Position

We are seeking a Principal Data Architect to define and lead the enterprise data strategy, architecture, and operating model supporting our healthcare platform and analytics ecosystem. This role will establish the target-state data architecture, governance frameworks, and cloud data platform strategy to enable scalable analytics, AI, and product innovation. As a senior technical leader, this individual will drive enterprise-wide data standards, influence executive stakeholders, and guide cross-functional teams in delivering secure, compliant, and high-performing data solutions in a regulated healthcare environment.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or related field required
10+ years of experience in data architecture, data engineering, or analytics platform design.
Proven experience designing modern cloud-based data architectures.
Strong expertise in: Data modeling (dimensional, canonical, domain-based)
Strong expertise in: Data lakes, warehouses, and lakehouse architectures
Strong expertise in: ETL / ELT pipeline design
Strong expertise in: Data integration and API-driven data ingestion.
Hands-on experience architecting data platforms using AWS services such as: Amazon S3, AWS Glue / Glue Catalog, Redshift, Athena, Kinesis, Lambda and RDS
Experience implementing data governance frameworks including: Data quality
Experience implementing data governance frameworks including: Metadata management
Experience implementing data governance frameworks including: Data lineage
Experience implementing data governance frameworks including: Master Data Management (MDM).

Nice To Haves

Master’s degree or MBA with a technology focus preferred
Experience working with healthcare data environments.
Familiarity with HIPAA and PHI data security requirements.
Experience with healthcare data standards such as: FHIR, HL7, EDI/X12
Background in enterprise or principal-level architecture roles
Experience scaling multi-tenant SaaS or B2B platforms in regulated industries
Proven success leading migrations (legacy to cloud, monolith to distributed systems, traditional BI to modern data platforms)
Relevant certifications (e.g., TOGAF, AWS Solutions Architect) preferred

Responsibilities

Define and own the enterprise data strategy aligned with business, product, and technology roadmaps.
Establish the target-state architecture for data platforms, analytics, and AI enablement.
Set architectural principles, standards, and guardrails across all data domains.
Act as the highest-level technical authority for data architecture decisions and trade-offs.
Drive long-term platform evolution, including cloud modernization and multi-tenant SaaS data architecture.
Define the architecture for scalable, cloud-native data platforms leveraging AWS services (e.g., S3, Glue, Redshift, Athena, Kinesis, Lambda, RDS).
Guide the design of systems supporting both operational and analytical workloads, including lakehouse and streaming architectures.
Establish reusable patterns for ingestion, transformation, storage, and data access.
Lead modernization of legacy data platforms to cloud-native, event-driven architectures.
Define enterprise integration patterns, including API-driven, event-driven, and streaming architectures.
Guide implementation of modern ETL/ELT and real-time data pipelines.
Optimize data flow for scalability, performance, and cost-efficiency.
Introduce flow-based prioritization models aligned with Agile practices such as SAFe (Scaled Agile Framework) where applicable.
Establish and institutionalize the enterprise data governance operating model.
Define standards for metadata management, data lineage, data quality, and stewardship.
Drive consistency in data definitions, semantic layers, and business metrics.
Partner with business and technology leaders to enforce accountability for data ownership and quality.
Define architecture standards ensuring secure, compliant handling of healthcare data (HIPAA, PHI).
Establish best practices for encryption, access control, data masking, and auditability.
Partner with security and compliance teams to proactively mitigate risk and ensure regulatory adherence.
Enable enterprise AI/ML capabilities through well-governed, high-quality data ecosystems.
Define architecture for feature engineering pipelines, model-ready datasets, and experimentation platforms.
Establish data readiness standards to accelerate adoption of advanced analytics and AI use cases.
Influence executive stakeholders on data strategy, investment decisions, and architectural direction.
Partner with Data Engineering, Product, Analytics, and Platform teams to align execution with strategy.
Mentor architects and senior engineers, elevating architectural maturity across the organization.
Lead cross-functional initiatives and resolve complex architectural challenges spanning multiple domains.