Principal Data Engineer

About This Opportunity

Our talent team is representing a confidential enterprise SaaS organization in their search for a Principal Data Engineer based in London. This is a senior technical leadership role where you'll architect and build the full stack of a modern data platform—from ingestion through transformation, storage, governance, and serving—at massive scale. Your work will underpin critical analytics and AI initiatives, enabling business users to leverage vast datasets in their workflows.

We're looking for a seasoned data engineer with deep expertise in distributed computing, data architecture, and production-grade software engineering. You'll tackle complex, high-scale challenges and set the technical direction for how data flows through the organization.

Responsibilities

• Lead data architecture, design, and deployment of scalable, high-throughput big data systems into production environments
• Architect, deploy, and manage foundational data systems including vector, NoSQL, and document databases that support AI infrastructure
• Develop end-to-end data engineering solutions: robust ETL/ELT pipelines, API services, and data ingestion frameworks
• Design and build storage and processing layers: data lakes, data warehouses, distributed file systems, and real-time streaming architectures
• Engineer feature-rich context pipelines that process large-scale enterprise data, balancing batch and streaming patterns
• Optimize and scale large distributed queries and data transformations for high performance and low latency
• Implement data quality frameworks to ensure data integrity, reliability, and governance across all data assets
• Collaborate with analytics, product, and platform teams to build data models capturing customer metrics, hierarchies, and relationships
• Stay current with the modern data stack, evaluating new tools, distributed computing frameworks, and database technologies

What We're Looking For

Required:

• Extensive data engineering experience with a strong track record of hands-on execution and delivery in complex data environments
• Deep practical understanding of database ecosystems powering AI and machine learning infrastructure (vector databases, NoSQL, document stores)
• Hands-on experience building, scaling, and shipping large-scale data platforms in production
• Deep practical experience with distributed data processing frameworks (Apache Spark, Flink, Hadoop)
• Strong expertise in message brokers and event streaming platforms (Apache Kafka, Kinesis)
• Extensive experience with workflow orchestration tools (Apache Airflow, Dagster)
• Hands-on expertise with cloud data warehouses (Snowflake, BigQuery, Redshift) and data lake architectures (Databricks, Delta Lake, Apache Iceberg)
• Advanced SQL skills and proficiency in Python
• Strong background in modern software development practices (testing, code review, CI/CD, Infrastructure as Code)

Desirable:

• Extensive, progressive experience leading technical projects and mentoring engineering teams
• Hands-on experience with cloud-native infrastructure (AWS, GCP, or Azure)
• Experience implementing data observability, monitoring, and alerting frameworks at scale
• Familiarity with enterprise planning platforms

How We Work With You

Candidates apply directly through Get A Job.ai. Our recruitment team will screen your application and conduct an initial interview. If there's a strong match, we'll submit your profile to our client for consideration. Please do not contact the client directly—all communication flows through our team to ensure a professional, coordinated process.

Pay

Compensation details will be discussed during the screening process and are competitive for a Principal-level Data Engineer in the London market.

Equal Opportunity

Get A Job.ai is committed to inclusive hiring practices. We welcome candidates of all backgrounds and provide reasonable accommodations throughout our recruitment process.