Abel Shiferaw

• Designed and maintained scalable data pipelines using SQL, Python, and internal tools to process large-scale datasets for Facebook feeds, ads, marketplace, and Instagram Reels. • Collaborated with cross-functional teams to translate business requirements into data solutions, improving data accessibility and insights for decision-making. • Optimized ETL workflows using Presto and Hive, reducing latency by 25% and enhancing data processing efficiency. • Implemented data quality checks and monitoring systems, ensuring 99.9% data accuracy and compliance with privacy and security standards. • Automated production processes, reducing manual intervention by 40% and improving operational efficiency.

• Led Snowflake-focused data architecture initiatives, unifying data management across Marketing, Finance, and HR teams. • Built scalable data pipelines using Snowpark, Snowpipe, and dbt, enabling near-real-time data ingestion and advanced analytics. • Orchestrated ETL workflows with Airflow, improving data integration and storage efficiency across AWS environments. • Conducted exploratory data analysis and transformations in Snowflake, delivering actionable insights from high-volume datasets. • Optimized dbt models, ensuring data quality and consistency across enterprise-wide projects.

• Designed and implemented scalable ETL processes on AWS, supporting daily decision-making for the Prime BI team. • Developed Python-based data engineering solutions, integrating seamlessly with AWS Glue, Lambda, and S3. • Implemented data governance and security protocols, ensuring compliance with GDPR and CCPA regulations, and reducing data breaches by 25% over a 12-month period. • Automated ETL workflows using Apache Airflow and Python, reducing manual intervention by 70% and increasing team productivity by 20%. • Collaborated with cross-functional teams (data scientists, analysts, and product managers) to deliver data-driven insights, resulting in a 15% increase in customer retention rates. • Built reporting solutions using Tableau and Looker, enabling stakeholders to make data-driven decisions. • Established SLAs for data delivery, improving reliability and reducing downtime by 30%.

• Built and optimized ETL processes using Google Cloud Data Fusion and Dataflow, integrating data for real-time analytics. • Productionized machine learning models using Vertex AI, enabling large-scale predictions and recommendations. • Implemented machine learning pipelines using TensorFlow Extended (TFX) to support predictive analytics models, contributing to a 15% increase in user engagement metrics. • Mentored junior data engineers and conducted knowledge-sharing sessions on best practices for data engineering, improving team productivity by 20%. • Designed and deployed dashboards using Google Data Studio and Tableau, providing stakeholders with real-time insights into key performance indicators (KPIs) and driving data-informed decision making. • Ensured compliance with data governance and security policies by implementing role-based access controls (RBAC) and encryption protocols, achieving 100% compliance with GDPR and CCPA regulations. • Ensured data governance and compliance using Data Catalog and Cloud IAM, enhancing metadata management and security. • Authored technical documentation, improving communication and alignment across engineering teams.

• Delivered lectures and workshops on data analysis tools, including SQL, Python, and Tableau. • Assisted professors in delivering Data Analytics course content, preparing lecture materials, and conducting review sessions for over 100 students per semester. • Developed and maintained course-related datasets, improving student engagement by 25%. • Utilized Python, R, and SQL to analyze and visualize data, creating interactive dashboards for classroom demonstrations. • Conducted weekly office hours, providing one-on-one support and contributing to a 15% increase in average assignment scores. • Designed and graded exams, quizzes, and homework assignments, ensuring timely feedback to enhance student understanding. • Mentored students, providing guidance on data cleaning, visualization, and statistical analysis. • Designed curriculum and real-world case studies, enhancing student comprehension and engagement.

• Designed and implemented a cloud-based data warehouse using Snowflake, improving query efficiency by 30%. • Built ETL pipelines with Airflow and dbt, transforming raw data into actionable models for dashboards and reporting. • Developed automated data pipelines using ETL tools and SQL, reducing manual reporting efforts by 40% and ensuring timely delivery of insights. • Provided guidance and training to junior data analysts, improving team productivity by 18% and fostering a culture of data-driven decision-making. • Delivered monthly and quarterly presentations to executive leadership, highlighting key trends, performance metrics, and actionable recommendations. • Implemented data validation and cleansing processes, reducing data errors by 25% and improving the reliability of analytical outputs. • Automated reporting workflows, reducing manual effort and improving report generation speed by 50%. • Collaborated with stakeholders to develop comprehensive data models, enabling self-service analytics.

• Managed analytics projects, overseeing data analysis, reporting, and dashboard development. • Conducted monthly performance reviews with senior leadership, presenting insights on revenue growth, operational efficiency, and customer satisfaction metrics. • Optimized ETL pipelines using tools like Apache Airflow and Talend, reducing data processing time by 25% and ensuring timely data availability for stakeholders. • Trained and mentored team members on advanced analytics techniques, SQL optimization, and data visualization best practices, enhancing team productivity by 20%. • Delivered a comprehensive customer segmentation analysis that informed targeted marketing campaigns, contributing to a 10% increase in lead conversion rates. • Developed technical specifications and data mining codes, improving data accessibility and accuracy. • Led the design and implementation of a data warehouse, enhancing data integration and reporting capabilities.

• Conducted financial analysis to support budgeting and forecasting for cybersecurity projects. • Performed risk assessments on financial data to identify potential vulnerabilities and ensure data integrity across agency systems. • Automated routine financial reporting tasks using Python and SQL, reducing manual workload by 30% and improving data accuracy. • Supported audit processes by providing accurate and timely financial documentation, contributing to a 100% compliance rate during internal and external audits. • Enhanced data security protocols for financial systems by collaborating with IT teams, ensuring adherence to federal cybersecurity standards and reducing data breach risks by 25%. • Developed dashboards and reports to track project performance metrics, improving decision-making. • Automated financial reporting processes, reducing manual effort and improving data accuracy.

The main focus of the masters program is mathematical and statistical techniques applied to financial markets. The courses taught in the program include, among others: - Financial Market Regulation, - Statistics and Econometrics, - Econometrics of Financial Markets, - Actuarial and Financial Mathematics, - Financial Engineering and Asset Management

The oikos Model WTO provides an opportunity for future decisionmakers to face important global issues in the simulation framework of the WTO ministerial negotiations. Every year since 1997, students from around the world have been invited to Switzerland to debate and exchange creative ideas in the realistic context of the World Trade Organisation. A multiplicity of cultures and interests is ensured through the participation of ten countries. Students represent nations by groups of six delegates. Each of them takes part in one committee. In total, six committees will engage students to actively debate on trade related issues through various perspectives. While delegates defend their national interests, two chairpersons in every committee try to lead them to an agreement. These key participants have received specific training at the University of St. Gallen before the negotiations. http://www.model-wto.org/Model_wto/Vision_and_mission.html