Data Squared Usa

reView is a distributed graph-native analytics and reasoning platform built on a microservices architecture. At its core is a semantic execution and verification system that transforms ambiguous analytical questions into explainable, governed graph computations.
This role focuses on building backend systems that preserve semantic correctness across ingestion workflows, graph execution, distributed services, and analytical reasoning paths.
In our platform, correctness is not just whether an API returns a response. Correctness means:

• graph relationships resolve to the intended entities,

• traversals preserve the meaning of the underlying data,

• derived computations remain explainable and reproducible,

• distributed workflows maintain consistency under load and failure,

• and analytical results are verifiably correct rather than merely plausible.

This is a backend and systems engineering role centered on graph execution, semantic reasoning infrastructure, distributed workflows, and correctness-oriented platform architecture.
The role is best suited for engineers who enjoy distributed systems, graph execution, query semantics, and correctness-oriented platform design.
Scope

• Backend and systems-focused engineering role

• Design and evolution of semantic execution, graph validation, and reasoning infrastructure

• Close collaboration with platform, ingestion, and graph engineering teams

• Containerized local development and shared staging environments for integration and execution validation

Leveling: At the mid level, you will implement and extend core platform behaviors and correctness mechanisms. At the senior level, you will shape execution semantics, system architecture, and how correctness is enforced across the platform.
Requirements
Semantic Execution & Backend Systems

• Design and implement backend services for graph execution and reasoning workflows

• Build and optimize graph traversal, query planning, and computation behaviors over connected datasets

• Develop validation and regression coverage for critical execution paths and service boundaries

• Contribute to execution semantics, identity resolution, and consistency guarantees across distributed workflows

Execution & Workflow Validation

• Validate end-to-end platform flows (ingestion → graph → query → result)

• Test distributed behavior under retries, partial failures, and asynchronous execution

• Ensure consistency and reproducibility across services and graph workflows

Data & Graph Validation

• Verify correctness and consistency of node and relationship creation in Neo4j / Memgraph

• Design mechanisms that preserve identity, traversal correctness, and semantic consistency across ingestion and execution flows

• Define and evolve graph test fixture strategies, including data seeding, isolation, and repeatability

Performance & Reliability

• Run recurring load and stress tests against ingestion, graph execution, and query workflows

• Identify and resolve bottlenecks across APIs, graph queries, and distributed execution paths

• Collaborate with engineers on scaling behavior in Kubernetes environments