Data Engineer

About Deliverance AI 

Deliverance AI is building the Enterprise AI Operating System — a platform that gives the world’s largest regulated organisations the trust and governance, cost control and ROI visibility, and production-grade infrastructure to operate AI at scale. 

We serve pharma, financial services, and telecoms enterprises with 5,000+ employees who have a board-level AI mandate but need a governed, production-grade platform to deliver on it. Our customers include global channel and enterprise partners, and our pipeline is growing rapidly. 

We are growing rapidly and this is a ground-floor opportunity to shape the future of enterprise AI. 

The Opportunity 

You will be deployed into enterprise client environments to build the data foundations that make AI work in production. This is hands-on, high-impact engineering — designing data pipelines, lakehouses, and vector databases that power AI agents across regulated industries. 

Your work directly enables enterprises to move from AI experimentation to production at scale. 

Every data architecture you build becomes a foundation for years of AI value. 

What You’ll Do 

• Design and implement data pipelines, lakehouses, feature stores, and vector databases for enterprise AI 

• Build the data foundations that power the Agent Library, SmartRouter, and knowledge architecture 

• Ensure data quality, governance, and lineage for regulatory compliance 

• Work with client data teams to modernise legacy data estates and make them AI-ready 

• Contribute reusable patterns, connectors, and data accelerators back to the platform 

• Operate within dedicated client delivery pods alongside SVAs and Agentic AI Engineers 

What We’re Looking For 

Must-Haves 

• 5–8 years in data engineering or data platform roles 

• Strong Python, SQL, and modern data stack: Spark, dbt, Airflow/Dagster 

• Experience with cloud data platforms: Snowflake, Databricks, BigQuery, or Redshift 

• Client-facing experience — comfortable embedded in enterprise environments