Senior Data Engineer (AWS)

Praca hybrydowa, Warszawa

B2B Kontrakt

Key Responsibilities

• Design and deliver cloud-native data and AI solutions on AWS across ingestion, storage, processing, orchestration, serving, and monitoring layers

• Build and optimize scalable data pipelines using AWS services (S3, Glue, Lambda, Redshift, Lake Formation, IAM, ECS/EKS) and tools like dbt and ETLeap

• Define reusable architecture patterns for batch, streaming, and near-real-time data processing

• Develop and operationalize ML workflows, including feature engineering, training support, deployment, monitoring, and lifecycle management

• Design and configure AI agents and reusable agent skills for data processing, analytics, quality checks, and automation use cases

• Use AI-assisted development tools (e.g. VS Code, Codex) to improve delivery speed and standardize engineering practices

• Collaborate with data scientists, engineers, and business stakeholders to translate requirements into scalable technical solutions

• Design APIs, microservices, and data services enabling ML and data products at scale

• Ensure alignment with data platform principles (data mesh, self-service, governance, enterprise architecture standards)

• Improve system performance, scalability, reliability, and cost efficiency across data and ML platforms

• Implement best practices in software engineering (CI/CD, IaC, testing, version control, documentation)

• Establish and maintain data governance capabilities (data quality, metadata, lineage, cataloging, compliance)

• Apply containerization and distributed system patterns (Docker, Kubernetes)

• Mentor engineers and promote reusable engineering and AI agent patterns

• Troubleshoot complex issues across data pipelines, cloud infrastructure, and ML systems

• Stay current with AI, LLMs, agent frameworks, and AWS technologies

Requirements

• 8+ years of experience in data engineering, solution architecture, or AI/ML engineering roles

• Strong hands-on experience with AWS data services and cloud-native architectures

• Proven experience building production-grade data pipelines and ML systems

• Advanced Python and SQL skills

• Experience with AI-assisted development tools (e.g. Codex, VS Code AI tooling)

• Knowledge of APIs, microservices, distributed systems, and DevOps practices

• Experience designing or working with AI agents or automation workflows is a strong plus

• Ability to work across technical and business teams in complex environments

• Strong communication and stakeholder management skills