Maria Travasso

Data Engineer with over nine years of experience building scalable ETL/ELT data pipelines and cloud data architecture using dbt, Snowflake, Talend, Apache Airflow, and Azure Databricks. Expert in Python automation, CI/CD integration, data quality frameworks, performance tuning, and data orchestration to reduce latency, lower compute costs, and enable reliable high-speed analytics. Proven track record modernizing legacy systems, optimizing data models, and delivering engineering-focused data solutions across AWS and Azure environments.

Freelance Data Engineer - Upwork - Remote

(2025-04 - 2026-02)

• Designed scalable ETL/ELT pipelines using Python, dbt, and Snowflake, reducing processing time by 40–60% for multiple clients.
• Orchestrated automated workflows with Airflow and Jenkins CI/CD in AWS, ensuring reliable, version-controlled deployments.
• Built high-volume ingestion from REST APIs and JSON sources into cloud warehouses, improving data freshness and availability.
• Optimized Snowflake performance via clustering and tuning, cutting compute costs by 30–50% while maintaining data quality.

Data Engineer - Wolfspeed - Durham, NC

(2024-01 - 2025-03)

• Built dbt models with Jinja/Python, streamlining analytics workflows and accelerating stakeholder access to insights.
• Orchestrated Airflow pipelines with automated validation, reducing data latency by 70% and enabling near real-time decision-making.
• Designed optimized tables/views for analytics, increasing query speed by 45% and empowering faster business decisions.
• Implemented automated data quality checks, improving accuracy by 30% and significantly reducing downstream errors.
• Mentored junior engineers and led design reviews, driving best-practice adoption and elevating team performance.
• Integrated REST APIs into Snowflake, reducing manual preparation by 40% and ensuring real-time data availability.

Data Engineer - Acara Solutions - Cary, NC

(2021-04 - 2023-11)

• Optimized ELT pipelines in Talend, increasing processing efficiency by 50% and delivering faster data to downstream analytics users.
• Architected staging/transformation/reporting layers, improving query performance by 40% and reducing long-term maintenance costs.
• Integrated dbt Cloud, Airflow, and Talend into CI/CD pipelines, enabling reliable deployments with zero downtime impact.
• Tuned clustering/performance, decreasing query times by 35% and improving responsiveness for business users.
• Established data quality frameworks, ensuring production reliability and minimizing data-related incidents.
• Collaborated cross-functionally to streamline ETL workflows, accelerating end-to-end processing and team productivity.

Data Engineer - HCL America - United States

(2019-03 - 2020-11)

• Engineered automated ETL pipelines for large-scale data, reducing manual effort by 50% and load time by 65%, delivering major operational time savings.
• Optimized Snowflake architecture (warehouses/clustering/storage), enhancing query performance by 45% while significantly lowering compute costs.
• Deployed quality checks and validation, cutting production data errors by 60% and building greater trust in data assets.
• Ensured accurate/timely data delivery to analytics teams, directly enabling faster and more informed business decisions.
• Built API integrations for vendor/SaaS ingestion, reducing retrieval time by 35% and improving data freshness for reporting.
• Developed Azure Databricks-based Spark pipelines to process high-volume datasets, improving ETL efficiency by 45% and enabling scalable handling.
• Integrated Azure Blob Storage with Databricks for secure ingestion and multi-agent processing, reducing storage costs by 35% and supporting LLM-ready data prep.

Technical Business Analyst / SQL Developer - Multimata LLC - United States

(2013-06 - 2019-02)

• Gathered requirements via stakeholder interviews and workshops, aligning solutions with state guidelines and business priorities to drive accurate project outcomes.
• Collaborated with cross-functional teams to gather requirements and design data structures/databases in SQL Server, enabling scalable data foundations for growing business needs.
• Developed stored procedures to strengthen data integrity/validation, reducing inconsistencies and improving system reliability for mission-critical reporting.
• Handled JSON data extraction/loading into SQL Server, ensuring accurate transformation/integration and seamless data flow across legacy and modern systems.
• Optimized SQL Server for databases and T-SQL procedures, accelerating ETL processes and reporting speed, resulting in faster insights for business users.
• Leveraged Azure Databricks for data processing and pipeline prototyping, accelerating development cycles and improving transformation accuracy by 40%.
• Utilized Azure Blob Storage with Databricks for secure data staging and multi-agent orchestration, enabling efficient handling of semi-structured sources.

Bachelor of Science in IT - Computer Science - Middle Georgia State University