> Markdown version of [/jobs/ext/2723034-staff-software-engineer-analytics-data-architecture](https://www.wearedevelopers.com/jobs/ext/2723034-staff-software-engineer-analytics-data-architecture). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Staff Software Engineer - Analytics & Data Architecture - **Company:** Ai, Inc - **Location:** United States (Remote available) - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Data Analysis, Databases, Data Architecture, Java Database Connectivity, JSON, Online Analytical Processing, Standard Sql, Data Streaming, Apache Spark, Database Performance, Data Layers, Build Management, Data Lakes, Apache Kafka, Free and Open-Source Software, Data Management, Vertica, Databricks - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/staff-software-engineer-analytics-data-architecture-oscilar-8999728 ## About the Role 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. ## Description 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. ## Related Videos - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Kubernetes and Microservices with Multi-Model Databases](https://www.wearedevelopers.com/videos/382-kubernetes-and-microservices-with-multi-model-databases) - [Tips and Tricks for Working with JSON](https://www.wearedevelopers.com/videos/1229-tips-and-tricks-for-working-with-json) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) - [Fault Tolerance and Consistency at Scale: Harnessing the Power of Distributed SQL Databases](https://www.wearedevelopers.com/videos/1146-fault-tolerance-and-consistency-at-scale-harnessing-the-power-of-distributed-sql-databases) - [Introducing JSON Structure](https://www.wearedevelopers.com/videos/100219-introducing-json-structure) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)