Fullstack data engineer

About this role

We’re looking for a hands-on
Full-Stack Data Engineer
who can build and scale modern data platforms end-to-end — from ingestion and transformation to AI-ready serving layers and consumption-ready data products.

This role combines data engineering, cloud infrastructure, and AI/LLM enablement, with strong ownership across the full data lifecycle.

What you’ll do

• Design and build scalable batch and real-time data pipelines
• Develop modern data platforms across ingestion, storage, transformation, and serving layers
• Build AI-ready pipelines for RAG systems, vector databases, embeddings, and agentic AI workflows
• Implement data models and lakehouse architectures
• Create APIs, semantic layers, BI-ready datasets, and other consumption-ready data products
• Apply DataOps best practices including CI/CD, testing, observability, monitoring, and lineage
• Collaborate with engineering teams and provide technical guidance/code reviews
• Work directly with stakeholders on technical discussions and solution delivery

Tech stack & experience

• Python
• AWS / Azure / GCP
• Databricks
• Kafka / Kinesis / PubSub
• Lakehouse technologies (Delta Lake, Iceberg, Hudi)
• Vector databases (Pinecone, Weaviate, pgvector)
• Data modeling (Star Schema, Data Vault)
• CI/CD for data pipelines
• Data observability & quality tooling
• AI-assisted development tools (Copilot, Cursor, Claude Code, Codex, etc.)

Nice to have

• Experience with AI/LLM infrastructure and RAG pipelines
• Exposure to MLOps and agentic AI systems
• REST APIs / semantic layers / embedded analytics
• Consulting or client-facing experience

What we offer:

• Competitive pay and salary growth based on your performance.
• Remote setup, B2B long-term contract, US EST working hours
• Dynamic working culture with opportunities to grow.
• Challenging projects with cutting-edge AI and cloud technologies.
• 100% paid sick leave.
• Friendly colleagues and a pleasant working atmosphere.

Looking for someone w...