Data Engineer

Role: Data Engineer (Fully Remote)

Conquer AI is building and scaling AI systems, and is looking for an engineer to own the data layer that feeds the models. The goal is to prevent downstream teams from debugging unreliable pipelines by ensuring data quality, lineage, and storage consistency.

Responsibilities

• Build and maintain batch and real-time data pipelines supporting the full AI lifecycle (ingestion → model training → serving)
• Ensure feature store and vector database consistency with the source of truth for retrieval and agentic systems
• Own data quality, reliability, and lineage across pipelines
• Design cloud data infrastructure and manage cost on the platforms Conquer AI runs on
• Create clear documentation and support data governance so downstream users can trust the data

Requirements

• Strong SQL and Python, with real pipeline engineering experience
• Comfortable with Spark or PySpark
• Experience with dbt and Airflow for orchestration
• Experience with at least one cloud platform: AWS, GCP, or Azure
• Experience with vector databases or feature stores (or ability to pick them up quickly)
• Treat data reliability as an engineering discipline (contracts, observability, lineage)
• Fluent English and comfort working async with a globally distributed team

Nice to have / Background

• Data Engineer or Senior Data Engineer from a tech company, scale-up, or AI-focused team
• Built pipelines other teams depend on without needing constant escalation

Offer

• Real ownership of the data layer for enterprise AI deployments
• Fully remote (any time zone)
• Direct exposure to infrastructure behind deployments for FTSE 100/250 and Fortune 500 clients
• Competitive compensation package including equity