Data Engineer (AI)

TL;DR

Data Engineer (Python/Azure): Building and optimizing data pipelines and infrastructure for a regulatory intelligence platform with an accent on turning unstructured data into AI-ready assets. Focus on designing scalable ETL/ELT processes, implementing data observability, and ensuring AI/ML workload readiness.

Location: Hybrid (London)

Company

hirify.global is a global RegTech business providing AI-powered SaaS solutions for regulatory compliance in the financial services industry.

What you will do

• Design and optimize data pipelines for structured and unstructured regulatory content across the platform estate.
• Convert raw source data into clean, reliable, and semantically consistent assets for AI and analytics consumption.
• Implement monitoring, alerting, and data quality checks to ensure pipeline observability and platform trust.
• Collaborate with architects and platform engineers to implement scalable architectural patterns.
• Support platform consolidation through source-to-target mapping and data migration work.
• Build infrastructure that supports AI/ML workloads, including feature engineering and model training.

Requirements

• 3+ years of experience in data engineering or a closely related role.
• Proficiency in production-quality Python and SQL.
• Hands-on experience building cloud data pipelines using ETL/ELT patterns.
• Experience with orchestration tools such as Apache Airflow, dbt, or Azure Data Factory.
• Strong understanding of version control and CI/CD practices.
• Must be based in London for a hybrid work arrangement.

Nice to have

• Experience with Microsoft Azure services (Synapse, Data Lake, Fabric).
• Familiarity with Apache Spark for large-scale data processing.
• Knowledge of data modeling (normalization, dimensional design) and governance practices.
• Experience with infrastructure-as-code tools like Terraform.
• Background in regulatory, financial services, or compliance data domains.

Culture & Benefits

• Fast-paced, high-performing "make it happen" culture that empowers ownership.
• Opportunities for rapid personal and professional development from day one.
• Collaboration within a global team spanning 19 countries across EMEA, Americas, and APAC.
• Chance to work with leading experts in AI research and engineering.