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Oscilar

Real-time fraud detection with no-code engine

Staff Software Engineer - Analytics & Data Architecture

Backend EngineeringConfirmed live in the last 24 hours
Full-timeRemote

About the Job

Requirements

  • Deep production experience operating a database or analytical store under concurrent, customer-facing load, including reasoning from a query plan to a fix.
  • Strong SQL skills and a sound understanding of columnar and OLAP execution.
  • Backend engineering skills and ability to read and modify a production codebase; the current stack is Java.
  • Experience designing or materially shaping a multi-tier data platform and defending design decisions with measurements.

Responsibilities

  • Find and fix database performance and scaling problems.
  • Own the schema and data model for analytical data.
  • Design and build a tiered analytics architecture spanning the system of record, a low-latency serving tier, and a batch and machine-learning tier.
  • Decide where workloads run across the tiers, using real benchmarks to support placement decisions.
  • Build observability into the data layer so problems surface early.
  • Partner with the ingestion team to keep read and write paths coherent as schemas evolve.

Desired Qualifications

  • Lakehouse experience with Databricks, Spark, Delta Lake, Iceberg, or comparable technologies.
  • Experience designing schemas for wide, semi-structured event data, including nested objects, maps, and JSON.
  • Streaming ingestion experience with Kafka or similar technologies.
  • A track record of a migration or major re-architecture, supported by cost and latency reasoning.
  • ClickHouse experience.
  • Connection-pool and JDBC-level tuning experience.
  • Familiarity with feature-flagged rollouts of query-engine behavior changes.
  • Open-source contributions to a query engine or related tooling.

About the Company

Oscilar

Real-time fraud detection with no-code engine

Oscilar operates in financial technology, offering a real-time fraud detection and risk management platform. It provides a no-code smart decision engine that combines machine learning and heuristic methods, enabling users to create and manage fraud rules and features through a user-friendly interface. The product works by letting financial institutions, e-commerce firms, and other businesses configure and deploy detection rules without heavy engineering effort, with real-time scoring and risk assessment fed by integrated ML models and heuristic checks. The company differentiates itself from competitors by focusing on a no-code rule-building experience, rapid rule creation and updates, and a subscription-based model that reduces the need for bespoke engineering work. Its goal is to help clients quickly implement and adjust fraud detection rules, enhancing operational agility and security while scaling with business needs.

Company size
201-500
Company stage
Early VC
Total funding
$20M
Headquarters
Palo Alto, CA
Founded
2021

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