> Markdown version of [/jobs/ext/2716132-software-engineer-data-platform](https://www.wearedevelopers.com/jobs/ext/2716132-software-engineer-data-platform). 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). --- # Software Engineer - Data Platform - **Company:** Cogent Inc - **Location:** San Francisco, CA, United States - **Experience:** Expert - **Salary:** $100,000.0 - $300,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Airflow, Batch Processing, Big Data, Databases, Data Integrity, Extract Transform Load (ETL), Data Retrieval, Software Design Patterns, Distributed Systems, Graph Database, Information Retrieval, Search Technologies, SQL Databases, Workflow Management Systems, Large Language Models, Database Optimization, Backend, Data Lakes, Kubernetes, Information Technology, Apache Flink, Apache Kafka, Search Engines, Terraform, Stream Processing, Data Pipelines, Docker, Databricks - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/software-engineer-data-platform-staff-cogent-security-8127334 ## About the Role * 5+ years of professional experience as a hands-on engineer and technical leader leading multiple projects * Experience building data pipelines for Information Retrieval Systems (such as knowledge graphs, search engines, or similar) for enterprise use cases * Experience in ETL orchestration and workflow management tools (such as Temporal, Airflow) as well as building batch processing and streaming systems with tools like Apache Kafka/Flink * Expert in database fundamentals, SQL, data reliability practices and distributed computing * Experience working fluently with standard orchestration & deployment technologies like Kubernetes, Terraform, Docker, Databricks, etc in multiple clouds ## Description We are looking for Founding and Staff-level Engineers to design and implement the foundational pillars of Cogent's data platform and integration pipeline in order to reliably ingest and normalize enterprise data sources across many corporate and IT systems and then to enable the transformation of that data into a knowledge base that can be leveraged by other GenAI systems., + Your role will involve building data connectors, running data pipelines, and extracting insights and context from our customer's enterprise environments. + You should get excited about building robust and secure backend systems that handle large volumes of data, ETLs, as well as reimagining how enterprise security teams should extract, store and access data. * Design highly performant data pipelines and indexing strategies that enable Applied AI use cases like semantic search and retrieval augmented generation + Work with Applied AI teams to taxonomize, correlate and deduplicate data across various enterprise sources, and architect indexing, storage and query strategies for data in Cogent's data lake. * Architect the modern data platform for Gen AI + The LLM stack and Gen AI landscape is changing everyday. You'll be front and center of making build vs buy decisions for various tools and services needed by the data platform, and integrating these decisions into our broader architecture and tech roadmap. + Implement generalizable design patterns and system components that allow us to scale from 1 integration to thousands of integrations ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Developing the Backend with Stefan Lingler, CTO at Shpock](https://www.wearedevelopers.com/videos/100360-developing-the-backend-with-stefan-lingler-cto-at-shpock) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [Nest.js - TypeScript in the backend can also be clean](https://www.wearedevelopers.com/videos/1033-nest-js-typescript-in-the-backend-can-also-be-clean) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [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) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence) - [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) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers)