Staff Data Engineer

Back in 2012, we were a group of engineers and designers who decided we wanted to build things—so we did. Able started as an engineering and product hub building for a portfolio of early-stage startups. We built many relationships while developing products that were thoughtful, effective, and genuinely useful. But, since then, we’ve grown… and so has our ambition. 

Now, we’re entering our next chapter—defined by applied AI. AI is a powerful force in the end-to-end software development cycle, and we’re creating practices that allow us to deliver software fast and more effectively than traditional approaches, creating meaningful value for our partners. Today, our builder mindset is driving us to become an AI-native organization across every function. We’re still evolving, and that’s part of the opportunity. If you want to build, learn, and tackle challenges alongside an ambitious team, let’s build together.

This position is 100% remote within LatAm.

We’re looking for a Senior Data Engineer to design and build scalable data systems that power analytics and decision-making. You’ll define how data is captured, build reliable pipelines, and ensure data is accurate, accessible, and ready to use.

• Design, build, and operate a Databricks medallion lakehouse architecture (Bronze/Silver/Gold layers) using Delta Live Tables to support ingestion, transformation, and serving of clinical, behavioral, and operational data across a multi-country digital health platform
• Architect and maintain scalable data pipelines on AWS (S3, Glue, Lambda, Kinesis, MSK/Kafka) that ingest data from diverse sources including FHIR-based clinical systems, remote patient monitoring devices, mobile applications, and third-party vendor APIs — ensuring reliability, idempotency, and observability at scale
• Implement multi-country data isolation and governance leveraging Databricks Unity Catalog, enforcing data residency requirements across different countries (e.g., the US, EU, and the Kingdom of Saudi Arabia) and integrating policy-as-code consent enforcement (e.g., Open Policy Agent) aligned with regulatory requirements and guidelines (e.g., HIPAA, GDPR)
• Partner with platform, compliance, and analytics teams to define and enforce data quality standards, lineage tracking, schema evolution strategies, and tamper-evident audit logging across all tiers of the lakehouse
• Support clinical data interoperability by implementing and maintaining FHIR-to-OMOP mapping pipelines, enabling downstream analytics, population health reporting, and AI/ML feature engineering on harmonized datasets
• Optimize data platform performance, cost, and reliability through partitioning strategies, compaction, caching, cluster sizing, and monitoring — targeting SLAs appropriate for a patient-facing healthcare platform operating at scale (e.g. 1M+ patients across a dozen markets)
• Contribute to certification and compliance readiness (e.g., ISO 27001, SOC 2 Type 2) by maintaining documentation, change control processes, and validation artifacts for all data infrastructure components
• Collaborate on real-time and event-driven architectures integrating Kafka-based streaming with the medallion layers and workflow orchestration, supporting adaptive patient journey logic and near-real-time analytics

• Requires 8+ years of data engineering experience, with deep hands-on expertise in Databricks (Delta Lake, Unity Catalog, DLT), AWS data services, Python/Spark, and streaming frameworks — preferably within healthcare, life sciences, or other highly regulated industries
• Strong proficiency with AWS data services such as S3, Glue, Lambda, Kinesis, Redshift, Athena, and IAM — with experience architecting end-to-end data pipelines in AWS-native or hybrid environments
• Advanced Python and PySpark/Spark development skills for batch and streaming ETL/ELT pipeline development, data transformation, and data quality enforcement
• Experience with streaming and event-driven architectures using Kafka (Amazon MSK or Confluent), including integration with lakehouse ingestion layers
• Proven ability to implement data governance frameworks including data lineage, schema evolution, access controls, cataloging, and audit logging at enterprise scale
• Strong understanding of data modeling for both analytical and operational use cases, including dimensional modeling, slowly changing dimensions, and schema-on-read patterns
• Experience with infrastructure-as-code (Terraform, CloudFormation, or CDK) and CI/CD pipelines for data platform deployments
• Familiarity with regulatory and compliance requirements in data management, including data residency, encryption at rest and in transit, and role-based access controls aligned with frameworks such as HIPAA, SOC 2, or ISO 27001
• Excellent collaboration and communication skills, with the ability to work cross-functionally with platform engineering, analytics, clinical, and compliance teams
• Bachelor's degree in Computer Science, Data Science, Engineering, or a related field (or equivalent practical experience)

• Experience with healthcare data standards and interoperability, particularly FHIR, OMOP CDM, HL7, and ICD-10, including building mapping or harmonization pipelines between clinical data models
• Experience supporting certification and audit readiness (SOC 2 Type 2, ISO 27001) through documentation, change control, and validation of data infrastructure
• Hands-on experience with multi-region or multi-tenant data architectures enforcing data sovereignty and residency requirements across multiple jurisdictions (e.g., US, EU, Middle East)
• Familiarity with policy-as-code approaches to data access and consent enforcement, such as Open Policy Agent (OPA) or similar engines
• Experience with workflow orchestration platforms and integrating data pipelines within broader application workflow contexts
• Exposure to real-time analytics and ML feature engineering on top of lakehouse architectures, including feature stores and serving layers
• Working knowledge of cost optimization strategies for Databricks and AWS, including cluster policies, spot instances, auto-scaling, and storage lifecycle management
• Experience in life sciences, pharmaceutical, or regulated healthcare organizations, particularly in patient-facing digital health or chronic disease management contexts
• Master's degree in a relevant technical field is a plus

Able is powered by curious, thoughtful people who care about what they build and how they build it. We’re actively investing in our team through AI training, knowledge-sharing, and hands-on experimentation to ensure everyone grows alongside the technology.

This position is 100% remote within LatAm. Strong verbal and written communication skills in English are a requirement. As a team member, you can expect:

• To work 40 hours per week, and be available during normal business hours as needed
• Payments made in USD
• 18 days of PTO per year, observance of local holidays, and an annual break between Christmas and New Years
• A monthly wellness stipend and snack boxes delivered to your home

Able builds technology products in a portfolio model. We believe that people, teams, and processes are more important than the ideas themselves, so we’ve focused on bringing great people together, and investing in their growth.

We’ve built products in a variety of industries. Everything from media to finance to toys to healthcare. Sometimes we work with management teams to help their businesses grow faster or unlock value using technology. Other times we start or buy businesses outright. Each time, we look for opportunities to leverage technology built at the portfolio-level to drive value faster.

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.

This is but the beginning of a conversation we’d love to have with you.

Apply, and let’s get this adventure started!