CRISTIAN ANDRES C.

Data Engineer and AI Engineer with 8+ years designing and shipping production data and AI systems for banking, retail tech and consulting clients in the US and LATAM. I cover the full path: ingestion, transformation, data modeling and reporting, and on top of that I build LLM products such as RAG pipelines, AI agents, evals and guardrails, on data platforms I build myself. 8 years of hands on Python, SQL and Power BI. 6 years across Snowflake, AWS, GCP, Azure, Terraform, Docker, CI/CD and Git. 2 years with Fivetran and Intuit or QuickBooks connectors for automated financial data ingestion. Used to working directly with business stakeholders in Agile and Kanban settings, owning initiatives from requirements discovery through implementation. English C1, remote first. CORE SKILLS Data platforms and warehousing: Snowflake (migrations, EDW design, Cortex AI), BigQuery, Redshift, Databricks, SQL Server, MySQL, dbt, dimensional and normalized data modeling, SQL performance tuning. Cloud: AWS (S3, Glue, Athena, Bedrock, SageMaker), Azure (Data Factory, Storage, Databricks, Azure OpenAI), GCP (GCS, BigQuery, Composer, Vertex AI, IAM), Terraform as infrastructure as code. Pipelines and DataOps: Python, Spark and PySpark, Airflow, Composer, Keboola, n8n, Fivetran, Jenkins, GitHub Actions, Bitbucket, Docker, Kubernetes, MinIO, web scraping. GenAI and AI engineering: Claude and OpenAI APIs, RAG, embeddings and semantic search, vector stores such as pgvector and Pinecone, AI agents and multi agent systems (MCP, Claude Agent SDK, LangChain, LangGraph), prompt engineering, guardrails, LLM as judge evals, fine tuning with LoRA and QLoRA, FastAPI serving, MLflow, PyTorch, scikit learn, Hugging Face. BI and analytics: Power BI (DAX, Power Query, dataflows, report performance), Sigma, Omni, Looker, Tableau, stakeholder facing dashboards and campaign analytics. Open to Data Engineering and AI Engineering roles.