Staff Software Engineer - Analytics & Data Architecture

Job summary

You will own the data layer and design the analytics architecture, including a tiered platform for system of record, low-latency serving, and batch/ML processing. You will also be responsible for database performance, schema modeling, and implementing observability to ensure system reliability.

Job details

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. 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

What you’ll do

You will own the data layer and design the analytics architecture, including a tiered platform for system of record, low-latency serving, and batch/ML processing. You will also be responsible for database performance, schema modeling, and implementing observability to ensure system reliability.

Requirements

Candidates must have deep production experience with analytical stores and strong SQL skills with a focus on OLAP execution. Proficiency in backend engineering and experience designing multi-tier data platforms are essential for this role.

Benefits

• Medical insurance • Dental insurance • Life insurance • Long-term disability insurance • Stock options • Monthly meal allowance • Professional development opportunities

Listed skills

• SQL · Preferred
• Java · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Database performance tuning
• Data architecture
• SQL
• OLAP
• Java
• Backend engineering
• Data modeling
• Observability
• Distributed systems
• Streaming ingestion
• Kafka
• Databricks
• Spark
• Delta Lake
• Iceberg
• ClickHouse
• ClickHouse DBMS
• Influencing Skills
• Influencing Without Authority
• Compliance Risk
• Confluent
• Dental Care
• Artificial Intelligence Risk
• Java (Programming Language)
• Artificial Intelligence
• Data Architecture
• Data Modeling
• Finance
• Query Planning
• Java Database Connectivity
• JSON
• Machine Learning
• Online Analytical Processing
• Online Transaction Processing
• SQL (Programming Language)
• Tooling
• Data Layers
• Low Latency
• Apache Kafka
• Codebase

Job areas

• Technology
• Data & Analytics
• Software
• Engineering
• Finance & Accounting
• Data Analytics Architect
• Data Analyst
• Statistical, Mathematical and Related Associate Professionals
• Business Intelligence Analysts
• Data Scientists