Data Platform Engineer

This is a fully remote position, open to applicants in Florida.

📋 Description

• Design and implement entity resolution strategies to eliminate duplicates and connect varied data into unified Golden Records.

• Create and sustain a global business knowledge graph and ontology for ownership chains, UBOs, and concealed risk relationships.

• Develop hybrid storage solutions that integrate graph databases with document and search repositories.

• Enhance real-time risk assessment and multi-layer ownership navigation to facilitate automated onboarding decisions.

• Architect and construct scalable data services and APIs for data ingestion, transformation, and delivery.

• Build and manage batch and streaming data pipelines using contemporary frameworks and AWS cloud-native tools.

• Ensure platform reliability, performance, monitoring, alerting, and participate in on-call responsibilities as necessary.

• Apply data modeling, quality assurance, lineage, and governance best practices.

• Work collaboratively with data scientists, analysts, and application engineers to convert requirements into platform functionalities.

• Promote automation and standardization through CI/CD, model as a service, and reproducible environments.

• Define and advance the data platform architecture, including contracts, SLAs, and versioned APIs.

⛳️ Requirements

• Proficient in Graph Ecosystems: Direct experience with Graph databases (e.g., Neo4j, AWS Neptune, or TigerGraph) and query languages such as Cypher or Gremlin.

• Demonstrated experience with Entity Resolution or Record Linkage (e.g., Senzing, Quantexa, or custom probabilistic matching algorithms).

• Capability to design adaptable ontologies for changing regulatory data.

• Experience in building GraphQL or REST APIs optimized for graph traversals and deep-tree lookups.

• Proven experience in creating centralized data platforms or data-as-a-service solutions at scale.

• Strong programming skills in Python, Java, Go, or Rust.

• Practical experience in building data pipelines and ETL/ELT workflows on a major cloud provider; AWS preferred.

• Familiarity with Spark/Flink, Kafka/Kinesis, Airflow or managed schedulers, and data warehouses like Snowflake, Redshift, BigQuery, or Databricks.

• Knowledge of CI/CD, Docker, Kubernetes, and Terraform.

• Strong emphasis on observability, resilience, and proactive alerting.

• Ability to collaborate effectively across functions and communicate with both technical and non-technical stakeholders.

• Nice to have: Experience supporting machine learning or real-time decision-making applications.

• Nice to have: Knowledge of AML, CTF, and KYC/KYB data frameworks, including LEIs and ISO 20022.

• Nice to have: Experience with global address normalization and geospatial indexing.

🏝️ Benefits

• Health Care Plan (Medical, Dental & Vision)

• Retirement Plan (401k, IRA)

• Life Insurance

• Flexible Paid Time Off

• 9 paid Holidays

• Family Leave

• Work From Home

• Free Food & Snacks (Orlando)

• Wellness Resources