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Senior Data Engineer (with AI)
Wroclaw Metropolitan AreaPosted 2 months ago
Full-timeonsite
Job Description
Requirements:
Experience
- 6+ years of hands-on engineering experience with production systems, not just building POCs.
- Full-stack mindset, comfortable across AI, Backend development, Data, and cloud infrastructure.
- Autonomous working style — you drive work forward without needing heavy process overhead.
- Experience adopting AI tools in day-to-day workflows (e.g. Claude Code, GitHub Copilot, or similar).
- Strong sense of ownership and proactivity; you spot problems before they're handed to you.
- Openness to broadening skills into adjacent areas.
- B2+ English, comfortable collaborating across distributed, multicultural teams.
Data Engineering
- Strong Python and SQL skills and solid software engineering fundamentals.
- Hands-on experience with Apache Spark for large-scale data processing.
- Proficiency with cloud data warehouse technologies: Snowflake, Redshift, or ClickHouse.
- Proven experience building batch data workflows with Apache Airflow or similar orchestration tools.
- Experience with real-time data processing using Kafka and streaming frameworks.
LLMs & Generative AI / MLOps
- Experience with LLM-based application patterns, including RAG architectures, prompt design, and agentic workflows.
- Basic understanding of embedding models, vector databases, and semantic search.
- Awareness of LLM evaluation techniques and quality assurance approaches.
- Experience deploying and maintaining ML models in production environments.
- Understanding of CI/CD practices applied to ML pipelines.
Cloud & Infrastructure
- Hands-on experience with AWS (SageMaker, Bedrock, Lambda, Glue, S3, ECR, or similar); GCP considered
Relevant cloud certifications are a plus.
Responsibilities:
- Design, build, and maintain robust data pipelines and ML systems for production environments.
- Develop and deploy ML and LLM-based solutions addressing real client business challenges.
- Build and maintain ETL/ELT workflows using modern orchestration and distributed computing tools.
- Implement MLOps practices: CI/CD, automated testing, model monitoring, and experiment tracking.
- Architect and implement cloud-native data and AI/ML solutions, primarily on AWS.
- Collaborate closely with Data Scientists, AI/ML Engineers, Backend Engineers, and client stakeholders.
- Participate in code reviews, contribute to technical documentation, and share knowledge within the team.
- Engage in client-facing discussions to understand requirements and propose technical solutions.
Why Provectus?
- Impactful work: projects span GenAI, MLOps, and NextGen data platforms for global enterprises across multiple industries.
- Senior-calibre peers: collaborate with top ML and Data professionals across North America, LATAM, and EMEA.
- Career growth: a clear path toward Tech Lead if you have the ambition — we actively develop our engineers.
- Recognised expertise: AWS Premier Consulting Partner featured in Forrester’s AI Technical Services Landscape.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.