Data Platform Engineer
Role details
Job location
Tech stack
Job description
Your Ideal Data Platform Engineer Job
- Are you passionate about powering the data behind AI-driven solutions?
- Do you thrive on solving large-scale data challenges across structured, semi-structured, and unstructured systems?
- Are you fluent in SQL, NoSQL, and distributed architectures?
- Can you design and optimize storage layers for both operational workloads and AI/ML pipelines?
- Do you want to shape the future of data infrastructure for an AI-first company?
- Are you excited to work with a high-trust, remote-first team committed to service, clarity, and innovation?, As a Data Platform Engineer at Quik!, you will be a cornerstone of our data architecture. You'll design, implement, and evolve scalable data systems that serve our product platform, internal engineering, and next-gen AI features. This role directly enables Quik!'s mission to deliver intuitive, intelligent forms automation. You will work closely with our Backend Engineers, DevOps, Product Owners, and the CTO to ensure performance, scalability, and availability of data systems while embracing modern tooling, cloud-native infrastructure, and AI-first practices.
What You'll Do
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35% - Data Architecture & Reliability
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Design and maintain scalable storage across SQL, NoSQL, in-memory, and search platforms
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Ensure system resilience, availability, and observability
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Implement lifecycle management, backup/recovery, and security protocols
30% - Performance & Optimization
- 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
20% - AI-First Data Practices
- 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
15% - Collaboration & Cross-Functional Work
- 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, At Quik! we continually celebrate the diverse community built by people with different backgrounds and perspectives. As an equal opportunity employer, we stay true to that by ensuring that our place can be anyone's place.
Requirements
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5+ years of experience managing or building large-scale data systems
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Proficient in SQL, NoSQL, and distributed systems (MSSQL, MongoDB, Redis)
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Comfortable with Elasticsearch or Solr, schema evolution, and data modeling
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Familiar with cloud-native infrastructure (AWS or Azure)
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Skilled in observability and performance tuning
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Excited to adopt AI-assisted tools to boost efficiency and quality
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Nice-to-Haves:
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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
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Experience with Kubernetes or container-based deployments
Benefits & conditions
- Salary: $135,000 - $155,000/year (commensurate with experience) + bonus potential
- Location: 100% remote (US based)
- Perks: Health coverage, paid time off, professional development, home office stipend