AI Data Engineer
About The Position
We are looking for an AI Data Engineer to lead the adoption of AI-assisted workflows within our engineering team. This role blends hands-on data engineering with the opportunity to reshape how we work — introducing agentic workflows, modern practices, and AI-driven productivity enhancements. You’ll work on building scalable data pipelines while also experimenting with AI tools, identifying opportunities to improve productivity, and helping the team transition to AI-augmented workflows. At Sigma Software, we deliver cutting-edge solutions for global customers, combining innovation with high-quality delivery. You will have strong leadership support, real space for experimentation, and the chance to influence engineering practices across the team.
Requirements
- 3+ years of commercial experience in data engineering
- Strong proficiency in SQL and Python (development and optimization)
- Hands-on experience with Spark/PySpark (Databricks is a plus)
- Experience with cloud data platforms (Azure preferred: ADF, Synapse, ADLS, Event Hub)
- Solid understanding of ETL/ELT, data modeling, and data warehousing
- Experience with orchestration tools (Airflow, ADF)
- Understanding of reliability, performance, and production-grade systems
- Hands-on experience using AI coding tools (Copilot, Cursor, Claude Code, etc.) in real workflows
- Experience delivering at least one project with AI-assisted development
- Ability to structure tasks for AI tools and critically validate their output
- Upper Intermediate level of English for effective communication
Nice To Haves
- Experience configuring AI development environments (agents, integrations, workflows)
- Familiarity with LLMs, embeddings, and RAG architectures
- Experience with vector databases (pgvector, FAISS, etc.)
- Familiarity with AI/agent frameworks (LangChain, LlamaIndex, etc.)
- Experience with dbt, Kafka, BI tools
- Data quality tooling (Great Expectations, Soda, etc.)
- Multi-cloud experience (AWS/GCP)
- Interest in advanced topics (evaluation, reranking, drift detection, synthetic data)
- Contributions to AI/data tooling or open source
Responsibilities
- Build and maintain scalable data pipelines using Spark, Databricks, and cloud platforms
- Design data models for analytics, ML, and AI applications
- Drive adoption of AI tools and agentic workflows within the data engineering team
- Identify and implement ways to improve engineering efficiency using AI
- Prototype and scale AI-assisted development practices
- Act as a go-to expert for AI experimentation and knowledge sharing
- Help establish best practices and contribute to an AI-focused community or guild
- Build pipelines supporting ML models, LLM applications, and AI workflows
- Ensure data quality, observability, and reliability
- Collaborate with Product, Data Science, ML/AI, and DevOps teams
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
