Lead Data Platform Engineer - AI Foundation (Remote - UK) at Jobgether

, , United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

02 Feb, 26

Salary

0.0

Posted On

04 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Platform Engineering, Machine Learning, Data Governance, SQL, BigQuery, Kafka, Data Modeling, Data Pipelines, Cloud Storage, Observability, Dimensional Modeling, Feature Stores, Data Quality, Performance Optimization, Streaming Platforms, CDC Tools

Industry

Internet Marketplace Platforms

Description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Lead Data Platform Engineer - AI Foundation in the United Kingdom. In this role, you will lead the design and development of a scalable, ML-ready data platform that serves as the foundation for AI-driven products and analytics. You will consolidate and optimize the data ecosystem, building batch and real-time pipelines while ensuring robust governance, security, and observability. Collaborating closely with ML and product teams, you will enable advanced AI capabilities and insights, transforming raw data into actionable intelligence. This is a high-impact role with significant ownership, allowing you to define architecture standards, improve data quality, and guide best practices across the organization. Your work will directly influence the performance, reliability, and AI-readiness of the platform, shaping the company’s AI-first strategy. Accountabilities: Architect, build, and maintain the foundational data platform to support AI and analytics workflows. Consolidate disparate data sources into a governed, ML-ready environment, including PostgreSQL, Kafka, BigQuery, and cloud storage. Develop and optimize batch and real-time data pipelines, ensuring low-latency, high-throughput performance. Implement data governance policies, including PII tagging, column-level security, and access controls. Build dimensional models and feature stores to support analytics and machine learning requirements. Establish monitoring and observability practices for data freshness, schema changes, and pipeline health. Collaborate closely with ML and product teams to enable AI feature deployment and ensure data platform alignment with business goals. Strong experience with GCP services: BigQuery, Dataflow, Cloud Storage, DataStream, AlloyDB/CloudSQL. Expert-level SQL proficiency and experience with dbt or similar tools for data modeling and testing. Hands-on experience with streaming platforms such as Kafka and Kafka Connect, and familiarity with CDC tools like Debezium. Experience building both batch and real-time data pipelines. Knowledge of dimensional modeling, data governance, and data quality monitoring practices. Understanding of observability frameworks, pipeline health monitoring, and performance optimization in BigQuery. Preferred: familiarity with ML feature stores, Vertex AI ecosystem, vector databases, semantic search, or prior experience in fintech or regulated data environments. Competitive salary and stock options. Private dental and health insurance. Access to the latest technology and tools for your role. 30 days of paid holidays (excluding bank holidays). Flexible work options: fully remote, hybrid, or office-based. Opportunity to work abroad for up to 4 months a year. High-ownership role with significant impact and autonomy. Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching. When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly. 🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements. 📊 It compares your profile to the job’s core requirements and past success factors to determine your match score. 🎯 Based on this analysis, we automatically shortlist the three candidates with the highest match to the role. 🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed. The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team. Thank you for your interest! #LI-CL1

Responsibilities

Lead the design and development of a scalable, ML-ready data platform for AI-driven products and analytics. Collaborate with ML and product teams to transform raw data into actionable intelligence.