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Senior Data Engineer, Data Platform - Hybrid Orlando
Build Worth AI’s graph-powered data platform for entity resolution, ownership mapping, and risk decisions. Design scalable APIs, pipelines, and cloud-native services for real-time data processing.
विवरण
- Create entity-resolution logic that produces unified Golden Records for businesses and individuals
- Build and maintain a global business knowledge graph and ontology covering ownership chains, UBOs, and concealed risk relationships
- Implement hybrid data storage using graph databases, document stores, and search platforms
- Tune the platform for real-time risk assessment and millisecond traversal across multiple ownership levels
- Develop scalable data services and APIs for data ingestion, transformation, and delivery
- Build and operate batch and streaming pipelines with modern processing frameworks and AWS cloud-native tools
- Manage platform reliability, performance, monitoring, alerting, and applicable on-call duties
- Apply sound practices for data modeling, quality management, lineage, and governance
- Partner with data scientists, analysts, and application engineers to turn requirements into platform capabilities
- Advance automation and standardization through CI/CD, model-as-a-service patterns, and reproducible environments
- Shape the data platform architecture with well-defined contracts, SLAs, and versioned APIs
आवश्यकताएँ
- Hands-on expertise with graph databases such as Neo4j, AWS Neptune, or TigerGraph, plus query languages including Cypher or Gremlin
- Demonstrated experience with entity resolution or record linkage using tools such as Senzing, Quantexa, or custom probabilistic matching
- Ability to create adaptable ontologies for changing regulatory data
- Experience developing GraphQL or REST APIs optimized for graph traversal and deep hierarchical lookups
- Background building centralized data platforms or data-as-a-service products at scale
- Strong software engineering capability in at least one of Python, Java, Go, or Rust
- Practical experience creating cloud-based data pipelines and ETL/ELT workflows; AWS experience is preferred
- Experience with Spark or Flink, Kafka or Kinesis, Airflow or managed schedulers, and warehouses such as Snowflake, Redshift, BigQuery, or Databricks
- Familiarity with CI/CD, Docker, Kubernetes, and Terraform
- Strong emphasis on observability, resilience, and proactive fault detection
- Ability to work across functions and communicate effectively with technical and non-technical partners
- Experience supporting machine learning or real-time decisioning use cases is a plus
- Knowledge of AML, CTF, and KYC/KYB data structures is a plus
- Experience with global address normalization and geospatial indexing is a plus
लाभ
- Medical, dental, and vision coverage
- Retirement savings options including 401(k) or IRA
- Life insurance
- Flexible paid time off
- Nine paid holidays
- Family leave
- Work-from-home support
- Complimentary food and snacks at the Orlando location
- Wellness resources
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