3 дня назад
Data Engineer IV (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Engineer IV (AI) (Data Platforms/AI): Designing and leading the build-out of a scalable, reliable, AI-ready data and analytics platform with an accent on automated pipelines, real-time analytics, and production AI/ML data products. Focus on building vector and feature stores, integrating LLM-adjacent workflows, optimizing cloud infrastructure, and enforcing security, governance, and compliance at scale.
Location: Glasgow, Glasgow City, United Kingdom
Company
develops cloud-based, AI-powered dental practice management, imaging, and revenue cycle automation software for dental organizations.
What you will do
- Architect and build AI-ready data pipelines and automated ELT workflows for real-time analytics, machine learning model serving, and generative AI applications.
- Lead the design of a modern data platform with vector stores, feature stores, LLM integrations, and AI-powered analytics infrastructure.
- Define data models and reliable data delivery in partnership with Product, Engineering, and Data Science.
- Establish engineering standards for version control, data quality, documentation, testing, and intelligent pipeline observability.
- Lead cross-functional data initiatives, shape the long-term data strategy, and mentor junior and mid-level data engineers.
- Optimize platform performance, cost, reliability, security, governance, and compliance, including HIPAA requirements.
Requirements
- 8–11+ years of data engineering experience with progression to senior or staff-level responsibilities.
- Expert SQL skills and proficiency in Python, Scala, or Java.
- Experience with data pipelines and ELT using Apache Spark, Airflow, dbt, or equivalent technologies.
- Experience designing cloud data platforms on AWS, Azure, or GCP, including data lakes, warehouses, and AI/ML platforms.
- Knowledge of data modeling, large-scale database optimization, real-time streaming architectures, and technologies such as Kafka or Kinesis.
- Hands-on experience with feature stores, vector databases, RAG or embedding pipelines, data governance, quality frameworks, and compliance requirements.
Nice to have
- Familiarity with HIPAA and other applicable regulations.
- Experience using AI development tools for engineering, code review, documentation, data modeling, and quality monitoring.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
Culture & Benefits
- Collaborative, empathetic, accountable, trustworthy, and ambitious working principles.
- Medical and dental insurance, life assurance, and income protection.
- 23 days of annual leave, 8 public holidays, company-paid sick time, and volunteer time off.
- Employee well-being program, technology stipend, referral program, and additional voluntary benefits.
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