Sigma Software
Information Technology And Services
AIDataEngineer
Neural analysis suggests this role is
optimal for mid candidates.
“AI Data Engineer at Sigma Software. Skills: Data Engineering, AI, Spark, Python, SQL, Cloud data platforms, AI tools, AI-assisted development. Build and maintain scalable data pipelines using Spark, Databricks, and cloud platforms. Design data models for analytics, ML, and AI applications”
Industry & Context.
problem-solving and critical thinking skills; critically validate their output
What They're Looking For.
Must Have
3+ years of commercial experience in data engineering, proficiency in SQL and Python (development and optimization), Hands-on experience with Spark/PySpark, 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 Have
Databricks is a plus, 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
What You'll Do.
Build and maintain scalable data pipelines using Spark
Design data models for analytics
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
How You'll Work.
Team & Collaboration
Collaborate with Product, Data Science, ML/AI, and DevOps teams; Collaborative and able to influence others
Communication Scope
Upper Intermediate level of English for effective communication
Process & Methodology
Ability to structure tasks for AI tools
Full Job Description
Are you ready to be a change-driver in the world of data engineering? 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. * 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 ## Qualifications * 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, a
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