Senior AI Data Engineer
Netwrix Corporation3 months ago
Kraków, PolandSenior
Responsibilities
- Design, build, and operate GitOps-driven data and AI platforms using GitHub, Azure DevOps, Terraform, infrastructure as code, automated testing, and CI/CD pipelines.
- Develop and maintain scalable ETL/ELT pipelines for model training, retraining, feature engineering, feature stores, and batch or near-real-time inference.
- Curate, index, and refresh enterprise data sources for RAG and internal AI agents, including embedding generation, vector database ingestion, and context retrieval flows.
- Implement monitoring for data quality, schema integrity, pipeline performance, data drift, model performance, and operational failure modes.
- Integrate security, privacy, compliance, lineage, ownership, and documentation controls into data and AI pipelines.
- Support MLOps workflows including model versioning, retraining, rollback strategies, observability, and production readiness.
- Build and operate Azure-based storage, compute, orchestration, and containerized services, while supporting hybrid or restricted environments.
- Collaborate with Product, Engineering, Security, Data Science, IT Operations, Solutions, and business stakeholders to translate requirements into durable architectures.
- Produce architecture diagrams, runbooks, operational handoff documentation, and recurring guidance for IT Operations and Solutions team members.
Requirements
- Bachelor’s degree in Computer Science, Data Engineering, Engineering, or equivalent practical experience.
- 5–7 years of experience in data engineering, platform engineering, or infrastructure roles.
- Strong proficiency in Python and SQL, with working fluency in JSON, YAML, and shell scripting.
- Experience using Git-based workflows, infrastructure as code, and CI/CD pipelines to operate production data and AI platforms.
- Experience operating workloads in Azure and AWS.
- Direct operational experience applying large language models and GenAI platforms, including OpenAI, Anthropic Claude, and Google Gemini, in enterprise-controlled environments.
Benefits
- Competitive health benefits.
- Continuous learning and development opportunities.
- Team-oriented, collaborative, and innovative work environment.
- Regular company town halls.
- Career growth and advancement opportunities.
- Remote-first work environment with frequent face-to-face interaction encouraged and facilitated.
- Equal opportunity employer with workplace accommodations available upon request.
Categories
Data EngineeringML Engineering