913 Data Engineer Senior Remote LATAM
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Job Location:
Monthly Salary:
Posted on:
21 hours ago
Vacancies:
1 Vacancy
Job Summary
Data Engineer (Graph Data Systems/Neo4j/Python/Entity Resolution) Senior Remote LATAM
We are partnering with a fast-growing healthtech startup that is building AI-native infrastructure for next-generation personalized and preventative healthcare.
They are developing an all-in-one clinical data platform designed for a new era of medicinewhere fragmented longitudinal and multi-modal health data becomes real-time actionable insights for clinicians and care teams.
This platform unifies records labs wearables diagnostics genomics and lifestyle inputs into a single coherent patient model. Early customers include leading functional integrative longevity and concierge medicine clinics helping shape the product from day one.
The mission: turn complex health data into clarity and action laying the foundation for predictive personal health models adaptive clinical intelligence and digital health twins.
Senior Data Engineer (Graph-Based Data Systems)
This role is ideal for an engineer who has strong experience with graph databases and thrives in building complex scalable data systems from the ground up. You will design the core graph architecture data lineage systems fuzzy matching engines and ingestion frameworks that power the future of healthcare intelligence.
Core Responsibilities
Graph Data Architecture
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Design and implement the companys core graph database architecture (likely Neo4j).
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Create advanced graph models representing patients biomarkers protocols events and relationships across multi-modal data.
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Enable high-context queries such as find patients with similar longitudinal patterns.
Data Normalization & Entity Resolution
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Build the entire normalization and deduplication engine.
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Implement fuzzy matching & entity resolution for unifying messy multi-source health data.
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Establish rules heuristics confidence scores and automated unification pipelines.
Metadata Lineage & Provenance
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Design a transparent lineage layer where every data point tracks:
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source
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timestamp
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reliability
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transformation path
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confidence scoring
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Ensure full traceability from ingestion storage computation.
Time-Series & Longitudinal Data Systems
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Architect storage optimized for high-frequency time-series signals (CGM wearables diagnostics).
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Support long-term longitudinal analysis across patient lifecycles.
API Layer & Query Engine
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Build APIs enabling complex graph queries and multi-relationship traversal.
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Support both real-time and analytical access patterns.
Multi-Source Health Data Ingestion
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Design ingestion for:
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clinical records (EHRs)
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labs
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wearables
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lifestyle/behavioral inputs
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continuous monitoring devices
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advanced diagnostics and genomics
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Unify this data into a structured high-quality canonical model.
Required Skills
Must-Haves
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Deep hands-on experience with graph databases (Neo4j or similar).
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Strong graph-based and relational data modeling.
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Experience with fuzzy matching & entity resolution algorithms.
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Experience in metadata lineage and provenance systems.
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Time-series data architecture and longitudinal data design.
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API design for complex multi-hop queries.
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Strong Python SQL.
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Solid system design especially around scalability and performance.
Nice-to-Haves
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Knowledge graphs or semantic data modeling.
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Built full data platforms end to end.
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Experience normalizing messy multi-source data.
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Kafka Pub/Sub or other streaming frameworks.
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Exposure to healthcare data: FHIR HL7.
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Experience with ML-driven feature extraction or enrichment.
What You Can Expect
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100% remote
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Full contractor engagement
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High-impact role with ownership from day one
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Work alongside a world-class founding team in healthtech and AI
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Build foundational infrastructure for the next decade of healthcare
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Fast-moving product-driven environment
Ideal Candidate
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Thrives in early-stage high-ownership environments.
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Loves building complex systems from scratch.
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Enjoys deeply technical challenges with real-world impact.
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Believes in the power of data to transform healthcare.
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
