Lead Data Engineer

🗓️ Working Days and Hours: Monday to Friday, 9 AM - 6 PM (UK Hours); Potential for Flexible Hours

📍 Location: Remote/Online

💷 Salary Range: Attractive, Top-of-Market Salary (paid in GBP/USD)

At Palm Outsourcing, we don't just fill seats; we build elite teams. We continuously partner with top-tier clients looking for exceptional international talent.

Opportunity Overview

Our client is building the operating system for modern property management, with an AI assistant that automates communications, compliance, maintenance, and scheduling across the UK property sector. Already live with pilot customers and scaling towards revenue, they are backed by experienced founders and investors. This is a rare chance to join early and own the data architecture of a fast-scaling AI company.

Role Description

As the founding data hire, you will architect and scale the data pipelines and infrastructure that power our client's AI and product systems. You will own data ingestion, transformation, and storage across operational and AI workloads, alongside vector search, retrieval, and machine learning pipelines. You will set the standards, governance, and hiring bar as the data function grows. This is a hands-on, high-ownership role suited to an engineer who enjoys building from the ground up.

Key Responsibilities

• Data Architecture - Architect and scale the pipelines and infrastructure powering our client's AI and product systems.
• Ingestion and Storage - Design and maintain data ingestion, transformation, and storage for operational and AI workloads.
• AI Data Systems - Build and optimise systems for vector search, retrieval, and machine learning pipelines.
• Reliability and Governance - Ensure data reliability, security, and governance consistently across the entire platform.
• Observability - Implement monitoring, observability, and data quality frameworks across all data systems.
• Founding Ownership - Define architecture, standards, and the hiring bar as the data function scales.

Minimum Qualifications

• English Fluency - Fluent, excellent written and spoken English is mandatory for this role.
• Data Engineering Experience - 7+ years of experience, mostly in dedicated data engineering roles.
• Pipelines and Distributed Systems - Strong experience designing and building data pipelines and distributed data systems.
• Relational Databases - Hands-on experience with relational databases, preferably PostgreSQL, MySQL, or similar.
• NoSQL and Vector Databases - Experience with NoSQL databases and vector databases used in AI systems.
• Python Programming - Strong programming experience in Python for building data engineering systems.
• Architectural Judgement - Proven ability to make and justify architectural decisions, not just implement them.

Bonus Qualifications

• Big Data Tooling - Familiarity with Apache Spark, Airflow, Kafka, and Elasticsearch or OpenSearch tooling.
• Cloud and AI Platforms - Experience with cloud infrastructure (GCP, AWS, or Azure) and machine learning platforms.
• Startup Experience - Experience with MongoDB, Pandas or Polars, and high-growth early-stage startups.

Benefits

• Top-of-the-market pay.
• Remote working.
• Potential for flexible hours.
• Becoming a part of Palm Outsourcing, where your performance is rewarded in long-term job security and continued growth opportunities.

Ready to elevate?

Hit apply, complete your profile, and let the right opportunities come to you.

Important Notes

1. Please note that this is a full-time position. Upon leaving your current role, you will be expected to provide professional references from your employer and update your LinkedIn profile accordingly.
2. Want to be considered for more than one job? Just apply once, and we constantly will match your profile across all our jobs. No need to apply twice unless your CV has materially changed, duplicate applications will result in older CVs being archived and your most recent CV being used.
3. Typically, we work with our own laptops, but if you need any extra gadgets to do your best work, we've got you covered.