PROFESSIONAL EXPERIENCE

Summary

Visionary and experienced Data Engineer with a proven track record of leading and collaborating with cross-functional teams to deliver high-impact data projects. Possessing 9+ years of experience in data engineering, business intelligence engineering, and business analysis, I have a deep understanding of the full lifecycle of data projects. Adept at driving innovation, improving performance, and exceeding customer expectations, I am now seeking a leadership role where I can leverage my skills to guide a team towards success and drive company-wide growth. With a strong commitment to personal and professional development, I am eager to take on challenging, influential projects that push me to expand my scope and make a lasting impact.

Amazon | Dec 2020 - Present

Data Engineer | Dec 2021 - Present

As a Data Engineer at Amazon, I utilized my technical skills to deliver impactful projects that optimized data pipelines, managed multiple AWS accounts and Redshift clusters, and ensured data privacy compliance. I was responsible for driving significant reductions in processing time for data pipelines, increasing team efficiency, and identifying infrastructure cost savings. My work also led to improved security, stakeholder satisfaction, and work output. Additionally, I created dashboards, reports, and automated deployment processes to support the team's success and achieve successful outcomes. Throughout my projects, I leveraged my expertise in SQL, AWS, and other internal tools and technologies to optimize the team's data management processes.

  • Redshift Optimization & Cost Savings
    Addressed a storage space issue on our Redshift cluster by evaluating the performance and costs of different configurations. By changing the node types to RA3, thus separating storage and compute, the storage problem was solved which allowed for a reduction in the cluster size, resulting in an annual cost savings of approximately $18k.
  • Duplicate/Unused Table Elimination
    Created a Python-based Lambda function to address the issue of duplicate and unused tables in the cluster. Utilized SQL and Python to track historical queries, compare tables, and perform a fuzzy match on table and column names. Resulted in 70TB of storage being cleared on the first run, leading to a significant improvement in storage and performance for the cluster.
  • ML Model Productionization
    Collaborated with Data Scientists to productionize and deploy their ML models to Amazon EMR and configure orchestration using AWS Lambda and AWS Step Functions. Used Jupyter notebooks, Apache Spark, Python, and AWS Step Functions during the deployment process. Successfully deployed new ML models and migrated existing models to this process.
  • DE Team Lead & Mentor
    Served as a Data Engineering Team Lead, managing a direct report and mentoring their transition from a BIE to a DE. Provided targeted training and guidance on projects to support their professional growth and development. Also, delivered regular training sessions to the larger BIE team, enhancing their technical skills and expanding their knowledge of Amazon's complex engineering landscape. Resulted in a well-rounded and high-performing analytics team, delivering reliable and impactful solutions for our stakeholders.
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Responsibilities
  • Data Pipeline Creation
  • Data Modeling
  • Performance Optimization
  • Architecture Design
  • Data Warehousing
  • Infrastructure Management
  • Technical Documentation
  • Technical Skills Development
  • Testing and Debugging
  • Interviewing/Hiring
  • Data Cleansing and Transformation
  • Code Review
  • Technical Support
  • Technical Leadership
  • Data Quality Assurance
  • Budgeting
  • Mentorship
  • Data Security and Privacy Compliance
  • Process Improvement

Business Intelligence Engineer | Dec 2020 - Dec 2021

As a Business Intelligence Engineer at Amazon, I leveraged my technical skills in SQL, QuickSight, Excel, and AWS to enhance the accuracy, consistency, and quality of data and reports. I automated manual processes, migrated a custom data lake to a more sustainable, AWS-based solution, and provided recommendations to ensure a smooth platform transition for driver behavior tracking. My work resulted in improved efficiency, security, and stakeholder satisfaction, and played a critical role in expanding important programs and making data management systems more performant and scalable.

  • Data Lake Migration to AWS
    Successfully migrated a custom-built data lake to a more sustainable and industry-standard solution on AWS, utilizing S3, AWS Glue, and Redshift Spectrum. Established naming conventions and standardized encryption, versioning, retention, and storage class policies for the data lake, reducing the time required to onboard new data sources.
  • Team-Level Data Pipelines & Standardized Reporting
    Improved accuracy and consistency of reporting by creating key data mart tables and utilizing QuickSight for standardized data visualization. Resulted in data marts being used in over 12 reports/dashboards and 100% utilization of standardized QuickSight formatting for partner-teams, leading to improved trust and buy-in from team.
  • Org-Level Weekly Business Review Dashboard (WBR)
    Migrated an org-level WBR from a manual Excel sheet to a fully automated QuickSight dashboard to ensure adoption and provide a quick insight into short and long-term trends, as well as comparison between programs and regions. Utilized QuickSight to create a standardized data pipeline, layout, calculated fields and visuals, which resulted in 80% adoption of the report by partner teams and it becoming the standard design for WBRs in the organization.
  • BIE Team Lead & Mentor
    Provided leadership to a team of eight BIEs, including two direct reports, delivering essential reporting and analysis to the Last Mile Trust and Safety org. Mentored and trained one team member, who was originally in a non-technical role, equipping them with the technical skills and stakeholder management knowledge needed to transition into a successful BIE role. Guided the other team member to a successful promotion to junior BIE through effective mentorship and training. Resulted in a well-rounded and highly skilled BIE team, providing valuable analytics to the Last Mile Trust and Safety org.

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Responsibilities
  • Data Warehousing
  • Data Modeling
  • Data Visualization
  • Dashboard/Report Building
  • Metrics Definition
  • KPI Definition
  • Stakeholder Communication
  • Business Requirements Gathering
  • Data Quality Assurance
  • Performance Optimization
  • Interviewing/Hiring
  • Data Governance
  • Statistical Analysis
  • Project Management
  • Cost Optimization
  • Technical Documentation
  • Code Review
  • Testing and Debugging
  • Data Cleansing and Transformation
  • Data Security and Privacy Compliance
  • Mentorship
  • Process Improvement

Crowd Cow | Feb 2018 - Dec 2020

Data Engineer / Business Intelligence Engineer

As a DE/BIE at Crowd Cow, I worked on projects aimed at improving the company's data ecosystem and decision-making processes. My responsibilities included creating and maintaining data models, designing and building data warehouses, and configuring Looker's LookML for business intelligence engineers and users to create dashboards and self-serve reports. I also worked on projects such as customer segmentation, inventory reporting, carrier analysis, and a daily business review dashboard. My work relied on various technologies, including SQL, DBT, TensorFlow, Python, Excel, and Looker, and resulted in improved efficiency, accuracy, and decision-making, leading to increased productivity and company growth.

  • Flexible Cohort Analysis
    Improved the business's ability to perform cohort analysis by adding cohort attributes to dimension and fact tables and configuring a LookML explore which allowed for easy customization of analyses without the need for predefined ETL scripts or complex SQL queries. Resulted in a reduction in time-to-insight for cohort analyses and improved decision-making.
  • Optimizing Email Marketing with ML
    Developed a machine learning model to optimize email marketing campaigns by predicting customers likely to make purchases in the next two weeks using TensorFlow, Python, and SQL for data analysis and manipulation. Resulted in an increase in customer engagement rate and sales revenue from email marketing.
  • Carrier Analysis Tool & Negotiation
    Built a tool to analyze shipping costs and make informed decisions on carrier selection. Analyzed shipping costs for national and regional carriers, considering billing structures and volume discounts. Used historical data and carrier rate structures for informed decision-making, resulting in a 15% reduction in shipping costs achieved through optimized carrier selection.
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Responsibilities
  • Data Pipeline Creation
  • Data Modeling
  • Data Warehousing
  • Data Visualization
  • Performance Optimization
  • Architecture Design
  • Infrastructure Management
  • Technical Documentation
  • Testing and Debugging
  • Data Cleansing and Transformation
  • Code Review
  • Metrics Definition
  • Interviewing
  • Dashboard/Report Building
  • KPI Definition
  • Stakeholder Communication
  • Business Requirements Gathering
  • Technical Leadership
  • Data Quality Assurance
  • Data Governance
  • Statistical Analysis
  • Mentorship
  • Project Management
  • Data Security and Privacy Compliance

Lowe's Canada / The Mine | Apr 2014 - Feb 2018

Data Engineer | Mar 2016 - Feb 2018

As a Data Engineer at Lowe's Canada/The Mine, I applied my technical skills to enhance the overall data management and reporting processes. I created new data pipelines, automated Excel dashboards, and designed and implemented a new data warehouse. I ensured data accuracy and consistency, improved the efficiency and usability of the reporting system, and maintained data privacy compliance. My work resulted in reduced processing time for data pipelines, improved security, stakeholder satisfaction, and work output, and relied on SQL, Data Warehouse Design, Python, and other related technologies to drive successful outcomes and enhance the company's data management processes.

  • Star Schema Data Warehouse
    Developed a star schema data warehouse to address issues with inconsistent metrics and definitions in BI reporting. Designed the architecture and implemented ETL processes to extract and load data from multiple sources into a centralized database. Utilized SQL scripts to preprocess and transform data into a star schema with fact and dimension tables, and created views for easy querying by the BI team. Resulted in a decrease in data accuracy bug tickets and improved trust and decision-making capabilities for stakeholders.
  • Python-Based Automation System
    Developed a Python-based automation system to update Excel dashboards overnight, utilizing various software tools and techniques including Python, Windows Task Scheduler, and Excel. Resulted in greatly improved efficiency and usability of the reports.
  • Snowflake Schema Data Warehouse
    Designed and built a snowflake schema data warehouse to improve quality and trust in BI reporting. Used SSIS processes to extract, transform and load data from multiple sources. Created SQL scripts to preprocess data into a snowflake schema and views with pre-built joins and aggregations to simplify queries. Resulted in a decrease in data accuracy bug tickets and improved decision-making capabilities for stakeholders.
Responsibilities
  • Data Pipeline Creation
  • Data Modeling
  • Performance Optimization
  • Architecture Design
  • Data Warehousing
  • Infrastructure Management
  • Technical Documentation
  • Testing and Debugging
  • Data Cleansing and Transformation
  • Code Review
  • Data Quality Assurance
  • Data Security and Privacy Compliance
  • Process Improvement

Business Intelligence Engineer | Jan 2015 - Mar 2016

As a Business Intelligence Engineer (BIE) at The Mine, I leveraged my technical and analytical skills to improve the efficiency and quality of data reporting. I created an Excel dashboard to track KPIs, streamlined the reporting process for business development teams, and created a macro-enabled excel template for report standardization. I used SQL, Power Query, VBA, and Excel to extract, transform, and load data, create visualizations, and streamline reporting processes. My work resulted in daily executive team viewing of KPIs, significant time savings for business development teams during vendor audits, and reduced time for creating new dashboards and reports for the BI team, leading to improved productivity and efficiency.

  • Executive Daily Business Review Dashboard
    Developed an Excel dashboard to track key performance indicators (KPIs), utilizing SQL and Power Query to ingest the data from the data warehouse. The dashboard was viewed daily by the executive team as the source of truth for company-wide KPIs.
  • Vendor Audit Dashboard
    Created an excel-based dashboard for business development teams to streamline vendor audits prior to contract negotiations. Utilized SQL, Power Query, and Excel for data extraction, aggregation, and visualization. Resulted in 30% time savings for business development analysts during audits and improved decision-making capabilities.
  • Excel Dashboard Template
    Developed a macro-enabled excel template for standardizing reporting processes across different projects. Designed and built the template utilizing VBA and Power Query, and trained team members on its use. Resulted in a reduction in time required to create new dashboards and reports, leading to improved productivity and efficiency for the BI team.
Responsibilities
  • Data Warehousing
  • Data Modeling
  • Data Visualization
  • Dashboard/Report Building
  • Metrics Definition
  • KPI Definition
  • Stakeholder Communication
  • Business Requirements Gathering
  • Data Quality Assurance
  • Performance Optimization
  • Data Governance
  • Statistical Analysis
  • Project Management
  • Cost Optimization
  • Technical Documentation
  • Code Review
  • Data Cleansing and Transformation
  • Process Improvement

Business Development Analyst | Apr 2014 - Jan 2015

As a Business Development Analyst at Lowe's Canada (as it pertains to my current career as a DE/BIE), I used my technical and analytical skills to improve the efficiency and effectiveness of data analysis and reporting. I created a web scraping script to collect brand data from competitor websites, developed a sales data set to enhance performance reporting for the Canadian platform, and built a PHP web application for cross-border program onboarding. I utilized Python, Selenium, Excel, SQL, HTML, CSS, jQuery, PHP, and MySQL to provide meaningful insights and streamline processes. These projects led to an increase in brands I managed, more comprehensive and accurate metrics for Canadian vendors, and higher brand onboarding in the cross-border program, resulting in enhanced data analysis and reporting capabilities and a thriving cross-border program.

  • Competitor Web Scraping Script
    Developed a web scraping script using Python and Selenium to collect data on brands from competitor websites with the goal of prospecting and onboarding new brands to the Lowe's Canada website. The resulting brand list was analyzed and cleaned using Excel, resulting in an increase in the number of brands managed from 25 to over 50.
  • Orders/Order Items Datasets
    Created orders and order items data sets using SQL to address the gaps in existing reporting tools, resulting in more comprehensive and accurate data sets that were used as the foundation for future data warehouse tables utilized in many reports throughout the company, increasing the efficiency and effectiveness of reporting and data analysis.
  • Cross Border Onboarding Web App
    Developed a PHP web application for cross-border program onboarding which resulted in a significant increase in brand submissions thanks to the streamlined onboarding process and improved visibility into the status of brand submissions, leading to increased brands on the program from 12 to over 100.
Responsibilities
  • Market Research
  • Vendor Audits
  • Project Management
  • Brand Development
  • Competitor Analysis
  • Client Engagement
  • Prospecting/Lead Generation
  • Account Management
  • Stakeholder Communication
  • Contract Negotiation