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Senior Data Engineer (with AI)

Provectus

Roles & Responsibilities

  • 6+ years of hands-on engineering experience with production systems
  • Full-stack mindset across AI, backend development, data, and cloud infrastructure, with autonomous, ownership-driven work style
  • Experience adopting AI tools in day-to-day workflows (e.g., Claude Code, GitHub Copilot, or similar)
  • Strong Python and SQL skills with hands-on experience in Apache Spark and cloud data warehousing (Snowflake, Redshift, or ClickHouse); experience building batch data pipelines with Airflow and real-time processing with Kafka

Requirements:

  • Design, build, and maintain production-grade data pipelines and ML systems (primarily on AWS)
  • Develop and deploy ML/LLM-based solutions addressing real client business challenges, including RAG architectures and prompt design
  • Implement MLOps practices: CI/CD, automated testing, model monitoring, and experiment tracking
  • Collaborate with Data Scientists, AI/ML Engineers, Backend Engineers, and client stakeholders; participate in code reviews and technical documentation

Job description

Provectus is a leading AI consultancy and AWS Premier Consulting Partner with 15+ years of R&D excellence. We deliver advanced solutions across AI, Data, ML, MLOps, and Cloud, with recognition from Forrester and AWS (FinServ AI Competency).


Partnering with innovators like Anthropic and Cohere, we build cutting-edge solutions—from LLM-powered applications to next-gen data platforms—across multiple industries.


As we expand in Poland, we’re looking for a Senior Data Engineer to join our EMEA team and drive high-impact AI and data projects alongside global experts.


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.
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