Rodrigo De Luna Lara

Experienced professional with a versatile background spanning 10 years of experience in several data roles:
► Analytics Engineer
► Data Scientist
► Data Engineer
► Cloud Engineer

Known for adaptability, independent problem-solving, and thriving in ambiguous projects.

Skilled in architecting and implementing effective, large-scale solutions across various domains.


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Senior Software Engineer (Data Engineer)

Data engineer within the marketing enablement initiative, responsible for shaping and delivering the data essential for informed decision-making across Etsy's marketing efforts.

Driving Incremental GMS - Implementing Google's Offline Conversion Import

  • Designed and executed a mission-critical data pipeline, leveraging Google's Offline Conversion Import to optimize bidding on Google Ads at an Etsy-wide account level. Resulted in incremental GMS growth totaling several million dollars for Etsy
  • I designed and implemented a comprehensive monitoring architecture to oversee daily runs and offer extensive troubleshooting data, ensuring high visibility into the reliability of this integration. This monitoring system enabled quick diagnosis of any issues, providing vital support for maintaining the integration's seamless operation and safeguarding Etsy's revenue.

  • Contributions to Etsy's Data Ecosystem

  • Played a pivotal role in enhancing the timeliness, quality, and reliability of data, resulting in improved campaign performance and increased user conversions through data-driven strategies
  • As the lead architect and developer, I proactively spearheaded the design and implementation of monitoring techniques within our data pipelines. This initiative was a collaborative effort, working closely with our team to ensure seamless integration and enhance our collective troubleshooting capabilities.

  • Data Integration Expertise

  • Collaborated closely with marketing analytics and performance marketing teams to navigate the diverse setups of third-party platforms like TikTok, Pinterest, AppsFlyer and Facebook.This often required leveraging specific client libraries or REST APIs to establish efficient data connections while seamlessly integrating data from our data warehouse to provide a comprehensive view of marketing performance.

  • Strategic Collaboration

  • Fostered collaborative relationships with channel leads to ensure data-driven decision-making.
  • Provided the necessary tools for performance marketing to diagnose and troubleshoot issues with their data.
  • Researched marketing needs and formulated a revenue protection strategy, ensuring the accuracy and integrity of critical data vital to marketing operations

  • Technical Responsibilities

  • Architected and developed data integrations using Google Cloud Platform (GCP) components, including BigQuery, Cloud Logging, Cloud Monitoring, PubSub, Cloud Functions, and Cloud Build.
  • Utilized Terraform to provision the necessary infrastructure, ensuring scalable and robust data pipelines.
  • Leveraged PHP and Python to create the required business logic, enhancing data processing efficiency.
  • Developed and optimized SQL scripts for data transformation in BigQuery, enabling actionable insights from raw data.

  • Tech Stack

  • Google Cloud Platform
    • BigQuery
    • Cloud Storage
    • Cloud Datastore (Firestore)
    • Cloud Functions
    • Cloud Build
    • Cloud PubSub
    • Cloud Logging
    • Cloud Monitoring
    • Cloud Scheduler
    • Cloud Tasks
    • IAM Management
  • Terraform
  • Python
  • PHP
  • Spark
  • SQL
  • Airflow
  • February 2022 - Present

    Data Engineer


    Data Engineering Consultant: Crafting Insights and Enhancing Data Solutions

    Company Solutions
    As a consultant specializing in marketing data solutions, I excelled in crafting versatile data pipelines and forging essential third-party connections. My primary responsibilities included:
  • Integration Expertise: I demonstrated proficiency in seamlessly integrating with external platforms, such as Pinterest and AppsFlyer. These integrations allowed for the acquisition of diverse data types, ranging from ad performance metrics to in-app event tracking and user installations.
  • Resource Provisioning with Terraform: Utilizing Terraform's capabilities, I efficiently provisioned Google Cloud resources, catering to data ingestion and processing needs. This resource management approach ensured scalability, cost-effectiveness, and agility.
  • Enhanced Data Warehousing: My contributions extended to designing and implementing integrations that facilitated the smooth flow of data into BigQuery from various sources. This consolidation enriched our data warehousing capabilities, offering a unified data repository for more comprehensive analysis.
  • Data Quality Assurance: I implemented robust data quality assurance protocols, ensuring the integrity and accuracy of incoming data. By establishing data validation processes and error handling mechanisms, I bolstered the reliability of our analytics, empowering data-driven decision-making across the marketing team.

  • Tech Stack

  • Google Cloud Platform
    • BigQuery
    • Cloud Storage
  • Terraform
  • PHP
  • July 2021 - February 2022

    Data Engineer

    Apex Systems

    Data engineering tech lead supporting AT&T:

    Company Solutions
    As the Data Engineering Tech Lead, I played an important role in delivering essential support to AT&T's Engineering teams.

    My contributions included architecting data pipelines, ensuring the smooth flow of ticketing data, and collaborating closely with Engineering teams to provide timely access to critical insights. This support empowered teams to make informed decisions, optimize operations, and enhance the overall customer experience:

  • Leveraging PySpark's capabilities, I developed custom scripts for hardware fault analysis using router logs and geospatial data, streamlining the troubleshooting processes.
  • I created specialized geospatial functions, using distance metrics for asset clustering. This enhanced AT&T's geospatial analysis capabilities, enabling more precise asset clustering and customer identification.
  • I used Natural Language Processing (NLP) techniques to develop string processing scripts to consolidated textual data, automating error detection and correction.
  • I developed scripts for raw text processing from log data by employing Regular Expressions. This analysis revealed hidden patterns, trends, and anomalies within the log data, offering critical insights into system performance.
  • February 2021 - July 2021

    Data Scientist

     GE Aviation

    During my tenure at GE Aviation, I provided instrumental support to internal teams across data engineering, data science, and scripting solutions. Some key highlights of my contributions included:

    Specialized Consulting Services

    Additionally provided consulting services to these customers:

    Company Solution
    American Airlines
    In my consulting role, I played a pivotal part in a collaborative venture between GE and American Airlines (AAL), focusing on the analysis of Minimum Maintenance Requirements (MMR) constraints. Some key highlights of my contributions included:

  • In-Depth MMR Analysis: Collaborating closely with scheduling and maintenance subject matter experts, I conducted a comprehensive analysis of MMR constraints specifically for the narrow body fleet. This involved a deep dive into data to ensure a thorough understanding of the constraints and their implications.
  • Actionable Insights through Data Visualization: Leveraging my data visualization expertise, I developed extensive visualizations aimed at helping the team gain a clear perspective on the impact of maintenance scheduling decisions on maintenance quality. These visualizations transformed complex data into actionable insights, facilitating informed decision-making.
  • Executive Presentation: I had the privilege of presenting the analysis findings to American Airlines executives. This presentation provided leadership with a comprehensive overview of the intricacies of MMR constraints and highlighted the significance of data-driven decision-making in optimizing maintenance operations.

  • The impact of this consulting engagement extended beyond the initial analysis. My data visualizations served as a powerful troubleshooting tool for addressing minimum maintenance requirements for the narrow body fleet. These visualizations not only guided immediate decision-making but also laid the foundation for a dedicated team of analysts within the company, ensuring the continued refinement and optimization of maintenance processes.
  • Automated Fault Code Extraction: I developed a custom Python script that demonstrated the power of automation in extracting fault codes from aircraft maintenance manuals. This innovation not only streamlined the data collection process but also reduced manual effort significantly. By automating this critical task, we ensured data accuracy and saved valuable time.
  • Dynamic Fault Code Visualization: To empower the team with insights into fault code trends over time, I created a dynamic dashboard. This visualization tool allowed stakeholders to track and analyze trends, facilitating informed decision-making. It provided a clear and interactive view of how fault codes evolved, offering valuable insights into common failures within the fleet.
  • Copa Airlines
    In collaboration with a User Experience (UX) specialist, I played a pivotal role in conducting a comprehensive discovery session for Copa Airlines. This session was instrumental in identifying and exploring digitalization opportunities that would propel the airline's operations into the future.

    Our collaborative effort focused on delving deep into Copa Airlines' processes, systems, and customer touchpoints. Through a series of intensive workshops and consultations, we engaged with key stakeholders, meticulously analyzing the existing landscape.

    Our objectives were twofold:
  • Discovery of Digitalization Prospects: Our foremost goal was to pinpoint opportunities where digitalization could be leveraged to enhance efficiency, customer experience, and overall operations. This involved identifying areas where technological innovations could bring transformative benefits.
  • User-Centric Approach: Our partnership with a UX specialist ensured that our findings were not only technologically sound but also aligned with the airline's commitment to providing an exceptional customer experience. We meticulously considered the needs and expectations of passengers, crew, and staff to ensure user-centric solutions.

  • This discovery session laid the foundation for a roadmap of digitalization initiatives, providing Copa Airlines with a clear direction for future technological investments. By identifying these opportunities, we aimed to usher in a new era of innovation and excellence for the airline, ultimately enhancing its competitive edge and customer satisfaction.
    Colombian Air Force
    Empowering Reliability Engineers through Python Training:
    In a teaching and mentoring capacity, I had the privilege of designing and delivering a comprehensive Python training program tailored specifically for reliability engineers within the Colombian Air Force. This initiative was aimed at equipping them with essential skills in Python programming and data analysis.

    My role extended beyond traditional training, encompassing the following key elements:
  • Customized Curriculum: I meticulously crafted a curriculum that catered to the unique needs and challenges faced by reliability engineers. The training covered fundamental aspects of Python programming, data manipulation, and analysis, ensuring participants gained practical, job-relevant skills.
  • Hands-On Learning: Recognizing the value of practical experience, I structured the training to include hands-on exercises and real-world examples. Participants had the opportunity to apply their newfound Python skills to real engineering scenarios, reinforcing their learning and enhancing their problem-solving capabilities.
  • Mentoring and Guidance: Throughout the training program, I assumed a mentoring role, providing guidance and support to participants as they navigated the world of Python programming and data analysis. This approach fostered a dynamic learning environment and encouraged participants to ask questions and seek solutions collaboratively.
  • Knowledge Transfer: Beyond the technical aspects, I focused on knowledge transfer, ensuring that participants not only acquired skills but also gained a deeper understanding of how Python could be leveraged to enhance their roles as reliability engineers.

  • This training initiative was instrumental in bridging the gap between engineering and data analysis within the Colombian Air Force, ultimately enhancing the efficiency and effectiveness of their operations.
  • Python-Powered Data Processing: I developed a sophisticated Python solution designed to efficiently process XML data adhering to ATA Spec 2000 standards. This solution seamlessly converted complex XMLs into structured tabular data, facilitating streamlined analysis and interpretation of critical maintenance information.
  • Automated Insight Discovery: Leveraging advanced reliability engineering techniques, I automated the process of insight discovery within the parsed maintenance data. This approach ensured that potential issues and opportunities were rapidly identified, enabling swift and data-informed decision-making.
  • Cost-Saving Discovery: Through meticulous data analysis, I identified a specific aircraft component that had been incurring high maintenance costs. This discovery was a pivotal moment as it represented the potential for substantial savings, amounting to millions of dollars. My findings served as a catalyst for strategic decision-making and resource optimization.
  • Industrias Peñoles
    I led a transformative initiative focused on data engineering and machine learning to address and analyze sulfur dioxide (SO2) spikes within a chemical plant.

  • Custom Data Engineering and Machine Learning Process: I spearheaded the development of a cutting-edge data engineering and machine learning process tailored specifically for the analysis of SO2 spikes. This process enabled the plant to gain deeper insights into critical environmental and operational parameters.
  • Python-Powered Data Preparation: I created custom Python scripts designed for data merging, cleaning, and preparation. These scripts streamlined the often complex task of data management, ensuring that the data used for analysis was accurate, consistent, and ready for advanced modeling.
  • Statistical Analysis of Operational Parameters: Leveraging statistical techniques, I conducted a rigorous analysis of various operational parameters in relation to SO2 spikes. This detailed examination allowed for a comprehensive understanding of the factors influencing SO2 levels and aided in the development of targeted mitigation strategies.
  • Infrastructure Development for Enhanced Analysis: Recognizing the need for robust data engineering infrastructure, I identified opportunities for improvement. My recommendations included the development of advanced data engineering tools and infrastructure, simplifying data analysis and enhancing the agility of the analytical process.

  • I played a pivotal role in enhancing the plant's ability to manage and mitigate SO2 spikes, ultimately contributing to a more sustainable and efficient chemical production environment.

    Scripting and Automation

  • ACARS Parsing Tool: Developed a Python-based executable tool for efficient parsing of ACARS data, enhancing data extraction and analysis.
  • Engine Management System (EMS) Query Wrapper: Engineered a Python wrapper simplifying data querying from the Engine Management System (EMS) platform, facilitating faster access to critical insights.
  • Automated Supply Chain Data Processing: Designed an automated solution for processing supply chain data, generating XLSX reports seamlessly, reducing manual efforts, and ensuring timely reporting.

  • Strategic Integration and Collaboration

  • Proof of Concept (PoC) for EMS and AirVault Integrations: Led the development of a Proof of Concept (PoC) to integrate the EMS and AirVault platforms, optimizing data workflows and operational efficiency, collaborating closely with key stakeholders.

  • Additional Roles and Responsibilities

  • Quality Management System Representative and Internal Auditor: Acted as a representative and internal auditor for the Quality Management System, ensuring compliance and adherence to industry standards.
  • Data Science Coding Standards Evangelist: Advocated for the importance of adhering to coding standards within the data science realm, fostering a culture of best practices and data quality.
  • Innovation Specialist: Served as an innovation specialist, actively promoting innovative solutions and approaches, contributing to a culture of continuous improvement and creative problem-solving within the team.

  • October 2018 - February 2021

    Data Scientist

     GE Oil & Gas

    Data scientist for the Turbomachinery and Power Solutions team

    During my tenure as a Data Scientist for the Turbomachinery and Power Solutions team at GE Oil and Gas, I played a central role in advancing innovative solutions and optimizing operations through data science:

  • Lead Developer for Fleet-Wide Monitoring Algorithms: I assumed a key role in developing fleet-wide monitoring algorithms for Heavy Duty turbines. These algorithms enabled comprehensive monitoring and analysis across the turbine fleet, enhancing operational efficiency and ensuring the reliability of critical machinery.
  • Analytic Development for Filter Change Recommendation: I designed and developed a an algorithm dedicated to Filter Change Recommendation. This innovative solution leveraged data insights to optimize filter change schedules, leading to cost savings and improved equipment performance.
  • Data-Driven Productivity Enhancement Tools: I actively contributed to the development of data-driven tools aimed at enhancing productivity and efficiency within the Turbomachinery and Power Solutions domain. These tools showcased the transformative impact of data science on operational processes.
  • Invention Disclosures: As an inventor and co-inventor, I made substantial contributions to the intellectual property portfolio of GE Oil and Gas. My involvement in six Invention Disclosures, including two Trade Secrets, underscored my dedication to pioneering algorithms for turbomachinery monitoring, which are instrumental in maintaining the reliability and performance of critical assets.
  • June 2017 - July 2018

    Analytics Engineer

     GE Power
    As an Alumni of the Edison Engineering Development Program (EEDP) for GE Power, I embarked on a journey marked by engineering excellence and analytics innovation. My contributions were shaped by a commitment to advancing operations in Turbomachinery for power generation:

  • Advanced Courses in Engineering (ACE): I successfully completed Advanced Courses in Engineering, focused on the intricacies of Turbomachinery operation for power generation. These courses equipped me with specialized knowledge critical to our field.
  • Performance and Analytics Team Rotations: During two one-year rotations with the Performance and Analytics team within Power generation services, I made impactful contributions, including:
    • Performance Monitoring Services: I provided diligent performance monitoring services for GE Power's valued customers in the Latin American region. This involved ensuring optimal operation and efficiency, contributing to enhanced power generation services.
    • Support for CM&U Proposals: I played a key role in supporting the development of conversion, modifications, and upgrades (CM&U) proposals. My analytical insights were integral in proposing solutions that optimized turbine performance and customer satisfaction.
    • Algorithm Development: I actively contributed to the creation and refinement of algorithms designed for power trending. These algorithms harnessed data analytics to enable predictive and proactive measures, ultimately enhancing the reliability and efficiency of power generation processes.
  • March 2015 - June 2017

    Software Development Intern

     GE Power
    During my initial role as an intern, I played a pivotal role in contributing to web development for an employee performance management system. My contributions extended to participating in and winning the Lean Challenge, a summer competition for college students, with a project aimed at identifying opportunities for upgrades in a fleet of gas turbines. My key responsibilities and accomplishments included:

  • Web Development Support: I actively supported web development efforts for an employee performance management system. This role involved working with technologies such as JavaScript and PHP, as well as incorporating front-end visualization libraries like HighCharts. Through my contributions, I contributed to the creation of a robust and user-friendly system.
  • Lean Challenge Success: Participating in the Lean Challenge, I successfully led a project that harnessed automation to streamline the process of identifying opportunities for upgrades across a fleet of gas turbines. This innovative approach significantly reduced the human effort required for the task. Our project was recognized and awarded, showcasing our team's ability to drive efficiency and innovation.
  • July 2014 - March 2015


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     Georgia Tech

    Master of Science

    Computer Science - Specialization in Interactive Intelligence

    GPA: 4.00
  • Advanced Courses in Machine Learning: I delved deep into the world of Machine Learning, gaining a profound understanding of algorithms, data modeling, and predictive analytics. These courses equipped me with the skills needed to develop and implement intelligent systems that can learn and adapt from data.
  • Exploration of Reinforcement Learning: I engaged in in-depth study and research in Reinforcement Learning, a subfield of artificial intelligence focused on decision-making and autonomous agent behavior. This exploration allowed me to grasp the complexities of training agents to make optimal decisions in dynamic environments.
  • Course Development: As a testament to my commitment to education, I took the initiative to develop a course on data visualization fundamentals. This endeavor allowed me to not only deepen my own understanding of data visualization but also share this knowledge with my peers, fostering a collaborative and knowledge-sharing environment.
  • 2016 - 2021

    Tecnológico de Monterrey

    Bachelors of Science

    Mechatronics Engineering

    GPA: 3.95

    High Academic Performance Scholarship

    Some of the notable accomplishments and projects from my undergraduate studies include:
  • Voice-Based Controls for Mabe Stoves: I embarked on a transformative project where I developed voice-based controls for Mabe stoves. This innovative endeavor showcased my proficiency in mechatronics, combining elements of mechanical, electrical, and software engineering. These voice-controlled stoves not only demonstrated cutting-edge technology but also offered enhanced convenience and accessibility.
  • Practice Manuals for ABB IRB 4000 Series Robot: My coursework included hands-on experience with ABB IRB 4000 series robots. Leveraging my understanding of robotics and automation, I developed comprehensive practice manuals for these robots. These manuals served as valuable educational resources, guiding students and professionals in mastering the operation and programming of these robotic systems.
  • Reviving Manufacturing Cell with Siemens PLCs (Step7): I undertook the challenge of restoring the functionality of a manufacturing cell that utilized Siemens Programmable Logic Controllers (PLCs) with Step7 software. Through systematic troubleshooting and expert programming, I successfully brought the manufacturing cell back to optimal operation. This accomplishment highlighted my proficiency in control systems and automation.
  • 2010 - 2014


    Programming Languages & Tools
    Other Skills
    • Machine Learning and Artificial Intelligence:
      • Supervised and Unsupervised Learning
      • Natural Language Processing
      • Operationalization of Machine Learning Models
    • Data Analysis and Visualization:
      • Exploratory Data Analysis
      • Visual Driven Insight Discovery
      • Visual Analytics
      • Data-driven Storytelling
    • Data Engineering and Integration:
      • On-premises and Cloud Data Engineering
      • RESTful API Integrations
      • Design of Data Processing Pipelines
      • SQL Scripting
    • Programming and Development:
      • Scripting (Python, PHP, R, Scala)
      • Library Development
      • Self-contained Applications
    • Project Management and Methodologies:
      • Agile Development and Scrum
      • Quality Management Systems
      • Six Sigma
      • Lean in Software Development

    Personal Interests

  • I enjoy film photography (some photos I've taken). I own these cameras:
    • Yashica Electro 35 GSN
    • Olympus OM-2n
  • I'm a fan of Star Wars and Avatar: The Last Airbender.
  • I collect Lego Star Wars starfighters, I have about 15 different sets, including some of my favorite fighters:
    • Tie Fighter
    • Tie Bomber
    • Tie Interceptor
    • Tie Defender
    • X-Wing
    • Y-Wing
    • A-Wing
  • I have 3 dogs, a Cocker mix, a Belgian Shepherd and a Dachshund.
  • I enjoy playing videogames on my free time. I've built my own gaming PC and I own a Series X.
  • I enjoy cooking any kind of cuisine, as well as fine dining and food tourism.
  • I also love traveling.

  • Certifications

    Logos provided by Clearbit

    • Google Cloud Certified Professional Data Engineer

    • Microsoft Certified Azure Data Scientist

    • Analytics Certified Engineer

    • Edison Engineering Development Program

    • Power Plant Fundamentals

    • Control System Fundamentals

    • Advanced Courses in Engineering

    • Green Belt in Six Sigma


    Logos provided by Clearbit

    • Emerging Engineer Award

    • Digital Engineering Excellence

    • Innovation That Inspires Others

    • CENEVAL National Prize

    • Magna Cum Laude

    • Social Service Award

    • Student Development Award

    • High Academic Performance (Dean's List)

    • Diploma in Management Skills