Our Story

Over the past several years, Able has grown immeasurably. We’ve also grown in the type of company that we are:

Chapter 1: We were founded in 2013 as a product and engineering hub for a portfolio of early-stage start-ups. We grew up as an in-house/external hybrid shared services model. That allowed us to hone our skills and establish our operational and cultural foundation.

Chapter 2: In 2019 we began to expand our vision. We began to grow outside of our inset partner base. We had good initial success meeting new partners, kicking off new relationships, and delivering high-value work.

Chapter 3: In 2023, we moved into the next phase of a new chapter, an expansion of the ambition of Chapter 2. Our strategy for growth centers around two audiences:

• Venture Capital. VC firms are looking for trusted product and technology solutions to distribute seamlessly across their portfolios at scale. The founders at their portfolio companies are looking for capabilities that can accelerate their businesses' go-to-market time, while minimizing cost and risk.
• Private Equity. PE firms are looking for trusted solutions that can catalyze growth for their portfolio companies at scale. The leaders of those companies are looking to leverage technology to unlock growth from their organizations.

Chapter 3a: We are now in the next phase of Chapter 3, aligned to our mission and vision, and accelerated by the powers of applied AI. We believe that AI will be a powerful force in the end-to-end software development lifecycle. Specifically we are creating practices that – coupled with our world class talent – can deliver software significantly faster than legacy techniques. The result is increased value for our partners, who can dramatically increase the capacity of their product organizations. 

Reporting into the Director of Engineering, the Data Architect will work cross-functionally with various team members across Able while having primary reporting alignment within the Engineering discipline.  This role will partner directly with client stakeholders and collaborate across disciplines, including Product, Design and Engineering to ensure data solutions meet business needs.  

Your Day-to-Day Responsibilities

Strategic Architecture Leadership

• Shape large-scale data architecture vision and roadmap across client engagements
• Establish data governance policies, security frameworks, and regulatory compliance standards
• Lead data strategy decisions around platform selection, integration patterns, and scaling approaches
• Guide organizations in data modernization initiatives and federated data model adoption

Client/Partner Value Creation  

• Lead technical discovery sessions to understand client's data landscape and business requirements
• Translate complex data architectures into clear value propositions for diverse stakeholders
• Build trusted advisor relationships to guide data strategy and technology decisions
• Align data architecture recommendations with client's business objectives and growth plans

Technical Architecture & Implementation

• Design and implement data architectures, including data lakes, warehouses, and federated systems
• Develop data integration patterns for real-time and batch processing across diverse data sources
• Create automated frameworks for data quality monitoring, validation, and lineage tracking
• Build reference architectures for common data patterns, including ETL/ELT pipelines and data mesh implementations
• Enable team success through knowledge sharing, mentoring, and documentation of best practices and compliance requirements

Business Impact & Solution Design

• Design and validate data architecture approaches through targeted POCs and pilot implementations
• Develop cost-optimized data solutions that balance performance, compliance, and scalability
• Transform business requirements into practical, production-ready data architectures
• Define and measure success metrics for data implementations and platform migrations

What we’re looking for

Ideally this candidate would have:

• 10+ years of data engineering experience, with at least 5 years focused on healthcare data systems 
• Extensive experience designing and implementing enterprise-scale data architectures, particularly federated data models across multiple domains and systems.
• Demonstrate deep understanding and practical implementation experience of regulatory compliance frameworks, including HIPAA, HITRUST, and GDPR, with the ability to apply these principles to general data security and governance.
• Experience with healthcare-specific standards (HL7, FHIR, DICOM) while also maintaining breadth in other industry-standard data formats and protocols.
• Proven expertise in building and maintaining large-scale data pipelines using modern data processing frameworks (Spark, Hadoop) and enterprise ETL/ELT tools (Informatica, Talend, or similar).
• Proficient in multiple programming languages including Python and SQL, with strong experience in both SQL and NoSQL databases at enterprise scale.
• Extensive experience with major cloud platforms (AWS/Azure/GCP) and their data services, including specific expertise with healthcare-related services and data engineering solutions.
• Demonstrate strong consulting experience, including stakeholder management, technical advisory, and ability to lead architectural discussions across various business domains.
• Must be able to design and implement data quality frameworks, validation processes, and monitoring systems across diverse data ecosystems.
• Strong leadership abilities with experience mentoring teams and driving technical strategy across multiple projects simultaneously.
• Experience with modern data catalog tools, metadata management systems, and data lineage tracking.

The following skills and experiences are considered an asset:

• A master's degree in Computer Science, Data Engineering, or a related field would be valuable but not required.
• Experience with real-time data processing systems and streaming architectures using technologies like Kafka, Kinesis, or similar platforms.
• Knowledge of machine learning operations and experience integrating ML models into data pipelines.
• Expertise in data mesh architecture and domain-driven design principles for data platforms.
• Previous experience in multiple industries beyond healthcare, demonstrating the ability to adapt data architecture principles across different business domains.
• Relevant certifications in cloud platforms, data engineering, or healthcare IT systems.
• Knowledge of international data privacy regulations and experience implementing compliant systems across different geographical regions.
• Background in performance optimization and cost management for large-scale data systems.

This position is 100% remote within LatAm.  Strong verbal and written communication skills in English are a requirement.  

Able's Values

• Put People First: We're caring, open, and encouraging.  We respect the richness that we each bring into our work.
• Imagine Better: We are optimistic in our outlook, as well as creative and proactive to deliver the highest quality.
• Expect Excellence: We commit to each other to always strive to be our best.
• Simplify to Solve: We create better outcomes by reducing complexity.
• We are all Builders: We are motivated and empowered to help build Able, and our partner's businesses.
• One Able. Many Voices: Our unity is our strength.  Our diversity is our energy.

Let’s build together.

Able is committed to inclusion and diversity and is an equal opportunity employer. All applicants will receive consideration without regard to race, color, religion, gender, gender identity, sexual orientation, national origin, disability, or veteran status.