---
title: 'Staff Software Engineer - Analytics & Data Architecture at Oscilar'
canonical: 'https://feeny.ai/job/staff-software-engineer-analytics-data-architecture-oscilar-canada-hsw3w0nswasm'
type: 'job'
last_seen: '2026-09-09'
---

# Staff Software Engineer - Analytics & Data Architecture at Oscilar

- **Company:** Oscilar
- **Location:** Canada
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-08-13
- **Last confirmed live:** 2026-09-09
- **Apply:** https://jobs.ashbyhq.com/oscilar/50e77792-0ce3-4333-9dd6-604bb7da6d8f

## Job description

Shape the future of trust in the age of AI At Oscilar, we're building the most advanced AI Risk Decisioning™ Platform. Banks, fintechs, and digitally native organizations rely on us to manage their fraud, credit, and compliance risk with the power of AI. If you're passionate about solving complex problems and making the internet safer for everyone, this is your place https://oscilar.com/careers.

Why join us:

- Mission-driven teams: Work alongside industry veterans from Meta, Uber, Citi, and Confluent, all united by a shared goal to make the digital world safer.
- Ownership and impact: We believe in extreme ownership. You'll be empowered to take responsibility, move fast, and make decisions that drive our mission forward.
- Innovate at the cutting edge: Your work will shape how modern finance detects fraud and manages risk.

## ABOUT THE ROLE

You'll own the data layer behind our analytics product and design of our analytics architecture and data model. Today that's a high-performance analytical store serving customer-facing queries; where we're headed is a tiered platform that separates our system of record, a low-latency serving tier, and a batch/ML tier. You'll keep the serving layer fast and reliable while designing and building that broader architecture, deciding where each workload lives based on measured latency, cost, and isolation.

This is a hands-on engineering role with strong architectural influence. You'll write code and also shape the multi-quarter direction of the analytics platform.

## WHAT YOU'LL DO

- Find and fix database performance and scaling problems.
- Own the schema and data model for our analytical data.
- Design and build our analytics architecture: a tiered platform spanning our system of record, a low-latency serving tier, and a batch/ML tier.
- Decide where each workload runs across those tiers, backing placement decisions with real benchmarks rather than vendor claims.
- Build observability into the data layer so problems surface early.
- Partner with the ingestion team to keep the read and write paths coherent as schemas evolve.

## WHAT WE'RE LOOKING FOR

Must-have

- Deep, production experience operating a database or analytical store under concurrent, customer-facing load: you can reason from a query plan to a fix, not just from documentation.
- Strong SQL and a real mental model of columnar / OLAP execution.
- Solid backend engineering. Our stack is Java, but we care more that you can read and modify a real codebase than which tools you've used.
- Data architecture experience: you've designed or materially shaped a multi-tier data platform and can defend those decisions with measurements.

Strongly preferred

- Lakehouse experience: Databricks, Spark, Delta Lake / Iceberg, or comparable.
- Experience designing schemas for wide, semi-structured event data (nested objects, maps, JSON).
- Streaming ingestion experience (Kafka or similar).
- Track record of a migration or major re-architecture, with the cost/latency reasoning to back the decisions.

Nice-to-have

- 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.

## BENEFITS

- Compensation: Competitive salary and equity packages, including a 401k plan
- Flexibility: Remote-first culture — work from anywhere
- Health: 100% Employer covered comprehensive health, dental, and vision insurance with a top tier plan for you and your dependents (US)
- Balance: Unlimited PTO policy
- Technical: AI First company; both Co-Founders are engineers at heart; and over 50% of the company is Engineering and Product
- Culture: Family-Friendly environment; Regular team events and offsites
- Development: Unparalleled learning and professional development opportunities
- Impact: Making the internet safer by protecting online transactions

## About Oscilar

## Company Overview
- **One-liner**: Oscilar provides an AI-native risk decisioning platform that uses agentic AI to help financial institutions manage fraud, credit, onboarding, and AML compliance in real time.
- **Entity Type**: Private (startup stage; funding rounds not publicly disclosed)
- **Headquarters**: Palo Alto, California, USA
- **Founded**: 2021
- **Founders**: Neha Narkhede (CEO) and Sachin Kulkarni (CTO)

## Core Business
- **Primary industry**: Financial technology (fintech) / Risk management / AI
- **Target customers**: Banks, fintechs, credit unions, and digital organizations (B2B, enterprise)
- **Mission**: “Making the internet a safer place for everyone” — empowering businesses to master risk, defeat fraud, and safeguard consumers in the era of AI.

## Products & Services
- **Oscilar AI Risk Decisioning Platform**: A unified, cloud-native platform that leverages agentic AI for detection, decisioning, and resolution across fraud, credit, AML, and onboarding. It processes over 30 billion decisions per year at peak throughput of 120,000+ requests per second with sub-100ms latency. Key components include:
  - **Agent Hub**: A coordinated suite of AI agents (e.g., Workflows, RuleRec, Credit Explainability, Analytics, TestGen, Fraud Disputes, AML L1, SAR, Narratives, Translator, Sanctions, PEP, CTR) trained on each customer’s SOPs and risk context. Agents define policies, score alerts, generate investigation narratives, and learn from analyst feedback.
  - **No-code policy engine**: Risk teams can define and deploy new policies in plain language without SQL or engineering support.
  - **Holistic risk dashboard**: Monitors the entire customer journey — onboarding, login, payments, compliance — in one place.
  - **Explainable decisions & full auditability**: Every decision is transparent and defensible for regulatory scrutiny.

## Market Standing
- **Valuation/Market Cap**: Not disclosed (private company)
- **Key Metric**: Processes 30B+ decisions per year; 120K+ requests per second; average latency <100ms. Employee count: ~104 (per Built In).
- **Notable Investors/Partners**: Not publicly listed from available sources. Advisors include Xin Ge (ex-CPO at Feedzai), Kevin Moss (ex-Chief Risk Officer at SoFi), Tomas Lobo (ex-Chief Technology & Risk Officer at Afterpay), and Rob Frohwein (co-founder of Kabbage, acquired by American Express).
- **Growth Signals**: Founded by Neha Narkhede (creator of Apache Kafka and co-founder of Confluent, NASDAQ: CFLT). Team built on deep risk experience from Meta, Uber, LinkedIn, Citi, and JPMorganChase. Currently hiring across multiple roles (33 jobs listed on Built In), indicating scaling. Remote-first culture supporting global talent acquisition.

## Competitive Advantages
- **Agentic AI tuned to customer data**: Models are trained on each institution’s own SOPs and risk patterns, retraining in days when patterns shift — not generic benchmarks.
- **Unified platform**: Covers fraud, credit, compliance, and AML in a single system, providing a holistic risk picture that competitors often address with siloed tools.
- **Low-latency, high-throughput architecture**: Proven at 120K+ req/s with sub-100ms latency, built by engineers who scaled 10-billion-requests-per-second systems at Meta.
- **Explainability & audit trails**: Full decision transparency for regulatory compliance, a critical differentiator for financial clients.
- **Feedback loop**: Analyst feedback continuously refines agent recommendations, improving over time.

## Strategic Focus
- **Deepen the Agent Hub**: Continue building and refining specialized AI agents for every risk decision type (fraud, AML, credit, sanctions, etc.).
- **Expand customer base**: Target more banks, fintechs, and digital organizations globally, with recent hires in sales and customer support (including Philippines office).
- **Maintain remote-first culture while scaling**: Leverage distributed talent to grow efficiently.
- **Invest in ML and generative AI**: Use cutting-edge tools to stay ahead of evolving fraud and compliance threats.

## Why Work Here
- **Remote-first culture**: Work from anywhere; company provides home office setup assistance.
- **Cutting-edge technology**: Opportunity to work on AI/ML at scale, tackling complex fraud and financial crime problems.
- **Elite team**: Collaborate with experts from Meta, Google, Uber, LinkedIn, Confluent, Citi, and JPMorganChase.
- **Values-driven**: Customer obsession, radical ownership, efficient growth, one team, bold vision with clear eyes.
- **Benefits**: Competitive salary and equity, unlimited PTO, comprehensive health/dental/vision insurance, regular team events and offsites, professional development opportunities.
- **Mission**: Direct impact on making the internet safer for legitimate customers and enabling financial institutions to grow confidently.

## Sources
1. [oscilar.com](https://oscilar.com) — Product overview, platform features, metrics
2. [oscilar.com/about-us](https://oscilar.com/about-us) — Leadership team, advisors, company origins
3. [oscilar.com/careers](https://oscilar.com/careers) — Culture, values, benefits, remote-first policy
4. [builtin.com](https://builtin.com/company/oscilar) — Employee count, year founded, job listings

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