Data Platform Engineer

Worth AI, Inc.; Orlando, Northern (FL, KY); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Health Plan

Retirement Plan

Life Insurance

Flexible PTO

9 holidays

Family Leave

Work From Home

Free Food & Snacks (Orlando)

Wellness Resources

Job summary

Worth AI, Inc. is hiring a Data Platform Engineer in Orlando hybrid role to design, build, and operate core data services powering products and analytics. You will own end-to-end data pipelines and APIs that ingest, process, and expose high-quality data for internal and external users.

You will collaborate with data scientists, analysts, and engineers to translate needs into robust platform capabilities, maintain SLAs, and push CI/CD and reproducible environments across teams.

Qualifications

• Graph DBs such as Neo4j, AWS Neptune or TigerGraph experience.
• Entity resolution or record linkage expertise.
• Flexible ontologies for regulatory data.
• GraphQL/REST APIs optimized for graph traversals.
• Data platform or data-as-a-service experience at scale.
• Strong software engineering in Python/Java/Go/Rust.
• Data pipelines on AWS; Spark/Flink and Kafka/Kinesis know-how.
• Airflow, Snowflake/Redshift/BigQuery, Databricks familiarity.
• DevOps: CI/CD, Docker, Kubernetes, Terraform.
• Observability, resilience, and early warning signals.

Responsibilities

• Architect and implement entity resolution to create Golden Records.
• Design and maintain a global knowledge graph and ontology.
• Bridge graph databases with document/search stores.
• Optimize for real-time risk assessment and onboarding decisions.
• Build scalable data services and APIs for ingestion and serving.
• Develop batch and streaming pipelines on AWS cloud-native tooling.
• Own reliability, performance, and API-first data platform.
• Enforce data modeling, quality, lineage, and governance.
• Collaborate with data scientists, analysts, and engineers.
• Advance CI/CD, model-as-a-service, and reproducible environments.
• Define the data platform architecture as an internal service.

Skills

Graph databases

Entity resolution

Ontology design

APIs for graphs

Data platforms / DaaS

Python

Java

Go

Rust

AWS data pipelines

Spark / Flink

Kafka / Kinesis

Airflow

Data warehouses

DevOps

Docker

Kubernetes

Terraform

Observability

Tools

Neo4j

AWS Neptune

TigerGraph

Senzing

Quantexa

Terraform

Docker

Kubernetes

Snowflake

Redshift

BigQuery

Databricks

GraphQL

REST APIs

Job description

Worth AI, a leader in the computer software industry, is looking for a talented and experienced Data Platform Engineer to join their innovative team. At Worth AI, we are on a mission to revolutionize decision-making with the power of artificial intelligence while fostering an environment of collaboration, and adaptability, aiming to make a meaningful impact in the tech landscape.. Our team values include extreme ownership, one team and creating reaving fans both for our employees and customers.

As a Data Platform Engineer, you will design, build, and operate the core data services that power our products and analytics. You’ll own end-to-end data pipelines and API services that ingest, process, and expose high-quality data to internal customers (data science, analytics, product, and other engineering teams) and external partners.

You’ll be part of a small, high-impact team that treats the data platform as a product with strong SLAs, and reliable self-service for internal and external users.

Responsibilities

What you’ll do:

• Architect and implement entity resolution logic to de-duplicate and link disparate data points into unified "Golden Records" for businesses and individuals
• Design and maintain a high-performance global business knowledge graph and ontology to map complex ownership chains, UBOs, and hidden risk relationships across international borders
• Implement a hybrid storage strategy that bridges graph databases for relationship mapping with document and search stores for rich metadata and adverse media content
• Optimize the platform for real-time risk assessment, ensuring the ability to traverse multiple levels of ownership in milliseconds to support automated "Go/No-Go" onboarding decisions
• Design and build scalable data services and APIs for ingesting, transforming, and serving data across the company
• Develop and maintain batch and streaming data pipelines using modern data processing frameworks and AWS cloud-native tooling
• Own the reliability, performance, and API first data platform, including monitoring, alerting, and on-call where appropriate
• Implement best practices for data modeling, quality, lineage, and governance to ensure trustworthy, well-documented datasets
• Work closely with data scientists, analysts, and application engineers to understand their needs and translate them into robust platform capabilities
• Drive automation and standardization through CI/CD, model as a service, and reproducible environments
• Help define and evolve the architecture of our data platform as a true internal service with clear contracts, SLAs, and versioned APIs

• Expertise in Graph Ecosystems: Hands-on experience with Graph databases (e.g., Neo4j, AWS Neptune, or TigerGraph) and query languages like Cypher or Gremlin
• Identity & Linkage Mastery: Proven experience with Entity Resolution or Record Linkage (e.g., using tools like Senzing, Quantexa, or custom probabilistic matching models)
• Schema Design: Ability to design flexible ontologies that handle evolving regulatory data (e.g., changing PEP definitions or Sanction list formats)
• API Performance for Graphs: Experience building GraphQL or REST APIs specifically optimized for graph traversals and deep-tree lookups
• Experience building centralized data platforms or “data-as-a-service” offerings at scale (e.g., at a large tech or cloud-native company)
• Strong software engineering skills in at least one language commonly used for data and services (e.g., Python, Java, Go, Rust)
• Hands-on experience building data pipelines and ETL/ELT workflows on a major cloud provider (AWS preferred)
• Experience with modern data stack tools such as Spark/Flink, Kafka/Kinesis, Airflow/managed schedulers, and data warehouses (e.g., Snowflake, Redshift, BigQuery, Databricks)
• Familiarity with DevOps practices: CI/CD, containerization (Docker), orchestration (Kubernetes), and infrastructure-as-code (Terraform)
• Strong focus on observability (metrics, logs, traces), resilience, and building early warning signals
• Comfort collaborating cross-functionally and communicating clearly with both technical and non-technical stakeholders.

Nice to Have

• Background supporting machine learning or real-time decisioning use cases from a platform point of view
• Compliance Domain Knowledge: Understanding of AML, CTF, and KYC/KYB data structures (e.g., LEIs, ISO 20022)
• Geospatial Data: Experience handling global address normalization and geospatial indexing for risk detection

** This role is Orlando based, hybrid position in our Winter Park Office.

• 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