Full-Time Data Architect

About Able:

Able has grown significantly over the past years. Initially, a hybrid shared services model, Able expanded its vision to encompass new partners in 2019. Today, Able's growth strategy focuses on Venture Capital (VC) and Private Equity (PE) firms, using AI to accelerate software development and increase partner value.

Role Overview:

Reporting to the Director of Engineering, the Data Architect will collaborate cross-functionally with product, design, and engineering teams. This role will partner directly with client stakeholders to ensure data solutions meet business needs.

Responsibilities:

• Strategic Architecture Leadership: Shape data architecture vision, roadmap, and governance policies.
• Client Value Creation: Understand client data landscapes, translate architectures into value propositions, and build trusted advisor relationships.
• Technical Architecture & Implementation: Design and implement data architectures, integration patterns, and automated frameworks.
• Business Impact & Solution Design: Validate architecture approaches, design cost-optimized solutions, and define success metrics.

Skills & Experience:

• 10+ years of data engineering experience, with focus on healthcare data systems.
• Expertise in designing and implementing enterprise-scale data architectures (particularly federated models).
• Deep understanding and practical implementation of regulatory frameworks (HIPAA, HITRUST, GDPR).
• Healthcare-specific standards (HL7, FHIR, DICOM) and other industry-standard data formats/protocols.
• Building and maintaining large-scale data pipelines using modern data processing frameworks.
• Strong proficiency in programming languages (Python, SQL) and databases (SQL and NoSQL).
• Experience with major cloud platforms (AWS/Azure/GCP).
• Proven consulting experience, stakeholder management, and architectural leadership.
• Experience in designing data quality frameworks, validation, and monitoring systems.
• Strong leadership, team mentoring, and technical strategy skills.
• Familiarity with modern data catalog tools, metadata management, and lineage tracking.

Additional Considerations:

• Master's degree in relevant field is valuable.
• Experience with real-time data processing, streaming architectures (Kafka, Kinesis).
• Knowledge of ML operations and integrating ML models into data pipelines.
• Experience with data mesh and domain-driven design.
• Experience in multiple industries (beyond healthcare).
• Relevant certifications.
• Knowledge of international data privacy regulations.
• Performance optimization and cost management skills for large-scale data systems.
• Strong verbal and written communication skills in English.

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