Gabriel Rullan Ferragut

As an adaptable Data Specialist, I've effectively partnered with Mapfre's Contact Center team, innovating tools to efficiently analyze and optimize the process of managing the Contact Centers and moving them from manual, hard to check and maintain data to fancy, automated and useful dashboards.

I prioritized working autonomously and delivering results within a short time frame. This hands-on approach facilitated swift process optimization and quick, tangible improvements to the sales strategy.

Recognizing the need for flexibility and results-oriented work, I ensured constant coordination with the team and delivered high-impact outcomes rather than focusing on hours worked. This approach led to enhanced efficiency and productivity in Mapfre's two high-performing Sales Contact Centers.

I take pride in my contribution, as the implemented strategies continue to drive value and improve sales processes at Mapfre.

🛠️ Tools (Data): SQL, BigQuery, Terraform, LookerML

🛠️ Tools (ETL): Python (pandas, numpy, APIs)

🛠️ Tools (Reporting): Excel, Looker

Skills: Data Analytics · Extract, Transform, Load (ETL) · Data Governance · Looker · Python

Dynamic Data Specialist: Bridging the Gap between Complex Analysis and User-Friendly Reporting

As a versatile Data Specialist, I've effectively collaborated with internal auditing teams, designing and developing innovative tools to swiftly analyze vast amounts of data. My expertise in data analysis, engineering, and science has allowed me to create interactive reports that seamlessly integrate multiple sources, showcasing trend analysis to easily identify outliers both in time and across various dimensions.

Recognizing the importance of a user-friendly experience, I have successfully collaborated with non-technical end users to ensure minimal barriers to entry while maintaining robust back-end functionality. This approach has facilitated the creation of adaptable ad hoc and semi-automatic testing protocols to detect suspicious occurrences, such as outdated data, excessive entries, behavioral imbalances, and other emerging needs.

I take immense pride in the results of my work, as the tools developed continue to drive value and enable continuous improvement. This is achieved through expanding testing protocols to existing areas, as well as applying the same innovative design to new domains.

🛠️ Tools (Data): SQL

🛠️ Tools (ETL): dbt, Python (pandas, numpy, APIs)

🛠️ Tools (Reporting): Excel, Power BI

As a dynamic Data Specialist, I have a passion for uncovering critical insights from data to drive informed decision-making, both past and future. My expertise in creating and maintaining data pipelines, business documentation, and interactive reports with tools like Tableau has empowered organizations to make data-driven decisions with confidence.

As a senior team member, I also have the rewarding opportunity to mentor and help the data team evolve and excel. Together, we successfully refactored the entire data structure—akin to changing parts of a plane mid-flight—without disrupting major processes. Our efforts led to the creation of two dozen reports that catered to the company's needs, and I was thrilled to guide a new team of junior members to take charge of the project, allowing me to transition to new challenges.

Data Engineering:

▪ Design and implement robust data systems and pipelines

▪ Streamline raw information from diverse sources

▪ Prepare data for comprehensive analysis

▪ Leverage data to identify automation opportunities

▪ Assess and address business needs and objectives

Data Analytics:

▪ Collect and interpret data for actionable insights

▪ Develop and maintain Business Intelligence dashboards

▪ Establish KPIs and metrics for business measurement

▪ Consult databases to extract key company information

▪ Collaborate with internal teams to identify process improvement opportunities

Data Team Leadership:

▪ Guide and supervise data analytics efforts

▪ Define tasks and objectives for team success

▪ Conduct periodic performance reviews

🛠️ Tools (Data): SQL, PostgreSQL, SQL Server

🛠️ Tools (ETL): dbt, Talend, Stitch, Microsoft SSIS, Python (pandas, numpy, APIs), AWS

🛠️ Tools (Reporting): Salesforce, Google Sheets, Tableau