Note: The job is a remote job and is open to candidates in USA. Quik! is an AI-first company revolutionizing paperwork through forms automation and integrations serving the financial services industry. The Data Platform Engineer will design, implement, and evolve scalable data systems supporting the product platform, internal engineering, and AI features. The role focuses on data architecture, reliability, performance optimization, AI-first data practices, and cross-functional collaboration.

Responsibilities

• Design and maintain scalable storage across SQL, NoSQL, in-memory, and search platforms
• Ensure system resilience, availability, and observability
• Implement lifecycle management, backup/recovery, and security protocols
• Identify and resolve bottlenecks across the data layer
• Tune indexing, caching, and partitioning strategies
• Improve query throughput and data latency for AI and transactional workloads
• Support AI-driven features with performant, accessible data structures
• Work on vector storage, semantic indexing, and future RAG (Retrieval-Augmented Generation) features
• Use AI-assisted tools (e.g., GitHub Copilot, ChatGPT) to improve development speed and documentation
• Partner with engineering teams to deliver backend features reliant on complex data pipelines
• Document schemas, systems, and best practices
• Mentor peers on observability and modern data design
• Taking full responsibility for uptime and optimization
• Collaborating proactively across disciplines
• Thinking ahead to support new AI product needs
• Owning documentation and cross-team communication
• Committing to continuous learning and sharing knowledge

Skills

• 5+ years of experience managing or building large-scale data systems
• Proficient in SQL, NoSQL, and distributed systems (MSSQL, MongoDB, Redis)
• Comfortable with Elasticsearch or Solr, schema evolution, and data modeling
• Familiar with cloud-native infrastructure (AWS or Azure)
• Skilled in observability and performance tuning
• Excited to adopt AI-assisted tools to boost efficiency and quality
• Experience with vector databases and semantic search
• Knowledge of RAG patterns or AI-first architecture
• Familiarity with streaming/event-driven platforms like Kafka or EventBridge
• Experience with Kubernetes or container-based deployments

Benefits

• Bonus potential
• Health coverage
• Paid time off
• Professional development
• Home office stipend
• 100% remote (US based)

Company Overview