Lead Data & AI Engineer

EPAM Systems; Amsterdam; Hybrid; EUR 110,000 - 150,000; Full time

Benefits offered by this job

26 paid holiday days

Pension plan

Disability insurance

Stock Purchase Plan

Commuting costs reimbursement

Laptop + corporate device

Bike lease

Employee Assistance Program

Learning & development opportunities

Employee referrals program

Job summary

EPAM Systems in the Netherlands seeks a Lead Data & AI Engineer to design and deliver advanced data solutions on cloud platforms. You will build scalable data pipelines, govern data quality, and enable ML feature engineering for analytics and intelligent applications in a hybrid work model.

You will lead architectures, collaborate with data scientists to deploy AI models, and drive reliability, security and cost efficiency across enterprise-scale data ecosystems.

Qualifications

• 5+ years of data engineering with leadership experience.
• Advanced SQL for large-scale performance tuning.
• Proficient Python for data workflows.
• PySpark expertise for distributed processing.
• Databricks experience with Delta Lake and optimization.
• Azure Data Factory orchestration of pipelines (ETL/ELT).
• AI/ML pipeline development and production model integration.
• CI/CD for data/ML pipelines (GitHub Actions, Azure DevOps).
• English proficiency at B2 level or higher.

Responsibilities

• Design and implement robust data architectures using cloud-native technologies.
• Build large-scale ETL/ELT workflows to process heterogeneous datasets.
• Create data models optimized for AI/ML pipelines and advanced analytics.
• Develop streaming and batch pipelines leveraging tools like Azure Data Factory and Databricks.
• Operationalize ML solutions, integrating feature stores and model endpoints.
• Collaborate with data scientists to deploy and monitor AI models in production.
• Integrate GenAI-assisted development methods into data workflows for automation.
• Ensure data governance, lineage, cataloging and quality across platforms.
• Optimize platform performance and cost efficiency while ensuring observability.

Skills

Data leadership

SQL performance

Python

PySpark

Databricks

Delta Lake

Azure Data Factory

AI/ML pipelines

GenAI workflows

CI/CD pipelines

Azure DevOps

English (B2+)

Tools

Databricks

Delta Lake

Azure Data Factory

GitHub Actions

Azure DevOps

Job description

We’re looking for a Lead Data & AI Engineer to join our team in the Netherlands in a hybrid working mode. In this role, you will design and deliver advanced data solutions and AI-assisted capabilities on modern cloud platforms. You’ll build scalable data pipelines, optimize data quality and governance and enable ML feature engineering for analytics and intelligent applications. The role requires hands‑on technical expertise in data engineering and AI integration while driving reliability, performance and security for enterprise‑scale systems.

Responsibilities

• Design and implement robust data architectures using cloud-native technologies
• Build large-scale ETL/ELT workflows to process heterogeneous datasets
• Create data models optimized for AI/ML pipelines and advanced analytics
• Develop streaming and batch pipelines leveraging tools like Azure Data Factory and Databricks
• Operationalize ML solutions, integrating feature stores, model registries and inference endpoints
• Collaborate with data scientists to deploy and monitor AI models using enterprise MLOps frameworks
• Integrate GenAI-assisted development methods into data workflows for automation and efficiency
• Ensure data governance, lineage, cataloging and quality frameworks across platforms
• Optimize platform performance, manage compute cost efficiency and enable observability for critical workloads
• Contribute to best practices, mentoring engineering teams in advanced data and AI engineering

Requirements

• 5+ years working in data engineering, with proven architecture and leadership experience
• Advanced proficiency in SQL for performance tuning at large scale
• Strong programming skills in Python, with applied experience in data engineering workflows
• Expertise in PySpark for distributed data processing
• Hands‑on experience with Databricks, including Delta Lake and performance optimization
• Knowledge of Azure Data Factory for orchestration of pipelines (ETL/ELT)
• Familiarity with AI/ML pipeline development, including integration of models into production
• Demonstrated exposure to Gen AI-assisted development workflows for accelerating data engineering tasks
• Strong knowledge of CI/CD for data and ML pipelines (GitHub Actions, Azure DevOps) and experience with large-scale environments
• English proficiency at B2 level (Upper-Intermediate) or higher

Nice to have

• Prompt Engineering knowledge and experience building RAG workflows
• Familiarity with Microsoft Foundry platforms
• Version control and CI/CD experience with GitHub
• Understanding of ETL/ELT optimization patterns beyond Azure stack
• Knowledge of data mesh or lakehouse architectural concepts
• Hands‑on exposure to dbt (data build tool), MKDocs and similar developer productivity tooling

We offer

• 26 paid holiday days
• Pension plan scheme
• Disability insurance (WGA Shortfall insurance)
• Long-term disability insurance (WIA Top up insurance)
• EPAM Employee Stock Purchase Plan (ESPP)
• Commuting to work - costs reimbursement
• Laptop + corporate simcard + corporate mobile device (subject to certain eligibility requirements)
• Bike lease
• Employee Assistance Program
• Corporate Programs including Employee Referral Program with rewards
• Learning and development opportunities including in-house training and coaching, professional certifications, and courses