Daniel Muller

I am a data engineer focused on building scalable data pipelines, analytical architectures, and data automation, with domain experience in financial operations, credit, and risk. I bring hands-on experience in Python, SQL, ETL/ELT, data modeling, data warehouses, API integrations, and data quality.

At Sicredi Vale do Piquiri I built and automated 100+ ETL pipelines, integrated internal systems and external REST APIs for near real-time credit monitoring, and implemented data validation and reconciliation frameworks that improved KPI reliability. I also automated reporting processes that reduced data delivery time by 40%.

Previously I developed a Customer 360 data platform consolidating data from SQL Server, PostgreSQL, and MySQL, designed a centralized data warehouse layer, and created end-to-end ETL pipelines and a PostgreSQL microservice to manage rules and proposal lifecycle. I contributed to data architecture and governance standards to improve cross-team consistency.

I hold an MBA in Big Data & Data Engineering and a Bachelor's in Computer Engineering, and I am actively expanding my modern data stack skills with dbt, Apache Airflow, Snowflake, and Terraform to deliver reliable, performant, and scalable data solutions.