About Me
Get to Know Me Better
About Me
I’m a Data Engineer and Analytics professional with over five years of experience building scalable, reliable data platforms across telecom, software, and financial services environments. My work focuses on turning complex, high-volume data into trusted, actionable insights that support business and executive decision-making.
My journey into data started with a strong foundation in computer science and a curiosity about how systems connect at scale. Over the years, I’ve specialized in designing end-to-end ETL pipelines, optimizing data workflows, and creating analytics-ready datasets using tools like Databricks, PySpark, SQL, Python, AWS, and Power BI. I enjoy working at the intersection of engineering and analytics—where clean data architecture meets real business impact.
How I Work
I believe in building data solutions that are not only scalable, but also maintainable and transparent. I prioritize data quality, performance, and governance from day one, and I’m intentional about documenting processes so teams can move faster with confidence. Having worked closely with product, finance, risk, and marketing teams, I’m comfortable translating business requirements into production-ready data solutions that scale.
What I Do
I design and optimize batch and analytical data pipelines, develop enterprise BI dashboards, and support advanced analytics use cases such as customer segmentation, churn analysis, and performance monitoring. I’ve led initiatives that improved processing efficiency, strengthened data reliability, and enabled leadership teams to make faster, data-driven decisions.
Beyond Work
Outside of day-to-day engineering, I enjoy learning new data technologies, refining system designs, and mentoring junior analysts and engineers. I’m always interested in improving how data teams collaborate, build, and deliver value—and I’m excited by opportunities that sit at the intersection of data, cloud platforms, and business strategy.
Work Experience
My Professional Journey
Senior Data Engineer – Analytics & Platforms
Discover Financial Services
•full-time- Lead the design and implementation of enterprise-scale ETL pipelines supporting ϐinancial transaction, customer behavior, and risk analytics datasets, processing millions of records daily with high reliability and performance.
- Architect and optimize Databricks and PySpark workϐlows to standardize ingestion, transformation, and aggregation layers, reducing batch processing times by over 45%.
- Partner closely with Risk, Fraud, Finance, and Product teams to translate regulatory and business requirements into scalable data models and analytics-ready datasets.
- Implement data quality frameworks, validation rules, and monitoring checks to ensure accuracy, completeness, and consistency across critical ϐinancial reporting pipelines.
- Drive performance optimization initiatives through query tuning, partitioning strategies, and Delta Lake best practices, improving downstream reporting performance by 40%.
- Mentor junior engineers and analysts, review code, and establish development standards to improve maintainability, scalability, and team productivity.
- Deliver executive-level dashboards and insights using Power BI, enabling leadership to monitor KPIs, trends, and operational risks in near real time.
Key Responsibilities:
- Designed and led enterprise-scale ETL pipelines for financial transaction, customer, and risk analytics data.
- Built and optimized Databricks and PySpark workflows for batch and analytical processing.
- Partnered with Risk, Fraud, Finance, and Product teams to translate business and regulatory requirements into scalable data models.
- Implemented data quality checks, validation rules, and monitoring processes across critical reporting pipelines.
- Developed analytics-ready datasets and Power BI dashboards for executive and operational reporting.
- Mentored junior engineers and analysts, conducted code reviews, and established development best practices.
- Documented data architectures, workflows, and governance standards to support long-term scalability.
Achievements:
- Reduced end-to-end data processing time by 45% through pipeline optimization and improved partitioning strategies.
- Improved data accuracy and reporting reliability by implementing standardized validation frameworks across financial datasets.
- Enhanced executive visibility into KPIs and risk metrics through scalable Power BI dashboards used by senior leadership.
- Improved downstream query performance by 40%, enabling faster decision-making across business units.
- Increased team productivity by setting engineering standards and mentoring junior team members.
Data Engineer – Analytics & Automation
Verizon Wireless
•full-time- Designed and maintained scalable ETL pipelines in Databricks and PySpark to integrate customer, survey, and transactional data from multiple enterprise systems.
- Developed optimized SQL queries using advanced joins, CTEs, and window functions to support analytics, reporting, and ad-hoc business analysis.
- Built and maintained interactive Power BI and Tableau dashboards with complex DAX calculations, parameters, and drilldowns to support leadership decision-making.
- Automated recurring reporting and data preparation workϐlows using Python and Excel VBA, reducing manual effort by over 60%.
- Implemented data validation and reconciliation processes to improve data accuracy and reduce downstream reporting errors.
- Supported advanced analytics use cases including churn analysis, customer segmentation, and anomaly detection using statistical and machine learning techniques.
- Collaborated with Marketing, Finance, and Engineering stakeholders to deϐine requirements, prioritize initiatives, and deliver scalable data solutions aligned with business goals.
- Produced clear documentation for pipelines, dashboards, and processes to support onboarding and operational continuity.
Key Responsibilities:
- Designed and maintained scalable ETL pipelines integrating customer, survey, and transactional datasets.
- Wrote optimized SQL queries using CTEs, window functions, and complex joins for analytics and reporting.
- Developed interactive dashboards in Power BI and Tableau to support leadership and operational teams.
- Automated recurring reporting and data preparation processes using Python and Excel VBA.
- Supported advanced analytics use cases including churn analysis, customer segmentation, and anomaly detection.
- Collaborated with Marketing, Finance, and Engineering teams to gather requirements and deliver analytics solutions.
- Created technical documentation for pipelines, dashboards, and automation workflows.
Achievements:
- Reduced data processing time by 40% by optimizing PySpark workflows and SQL queries.
- Cut manual reporting effort by 60% through automation using Python and Excel VBA.
- Improved dashboard adoption and usability by delivering interactive, drill-down analytics for leadership teams.
- Increased data accuracy and consistency through automated validation and reconciliation processes.
- Enabled data-driven customer strategy decisions through churn and segmentation analytics.
Business Intelligence Analyst
Flexera Software
•full-time- Delivered enterprise BI solutions by transforming and analyzing large-scale SaaS usage and ϐinancial datasets using SQL, Databricks, and PySpark.
- Developed optimized SQL queries and reporting views, reducing data retrieval and refresh times by 30%.
- Designed and deployed Tableau dashboards with interactive ϐilters and calculated fields to track KPIs, trends, and operational performance.
- Supported executive and ad-hoc reporting through Excel automation and Python-based exploratory data analysis.
- Conducted data validation, QA checks, and reconciliation to ensure reporting accuracy prior to executive distribution.
- Worked closely with product managers, ϐinance teams, and senior analysts to gather requirements and deliver actionable insights.
- Authored technical and functional documentation to improve knowledge transfer and reporting consistency across teams.
Key Responsibilities:
- Analyzed and transformed large SaaS usage and financial datasets to support business intelligence reporting.
- Developed optimized SQL queries and reporting views to support recurring and ad-hoc analysis.
- Designed and deployed Tableau dashboards with interactive filters and calculated fields.
- Supported executive and stakeholder reporting using Excel automation and Python-based analysis.
- Performed data validation, QA checks, and reconciliation prior to report delivery.
- Collaborated with product managers, finance teams, and senior analysts to gather reporting requirements.
- Authored documentation to improve reporting consistency and onboarding efficiency.
Achievements:
- Reduced report refresh and data retrieval times by 30% through SQL optimization.
- Improved reporting accuracy by implementing structured QA and validation checks.
- Delivered executive dashboards that improved visibility into SaaS performance and operational KPIs.
- Streamlined onboarding by creating reusable documentation and reporting standards.
- Strengthened stakeholder trust through consistent, high-quality reporting and insights.
Skills & Expertise
A Comprehensive Overview of My Technical Skills and Tools
Ai Ml
6Backend
5Cloud
5Database
6Design
3Devops
4Frontend
3Other
4Soft Skills
6Testing
5Tools
6Education
My Academic Background
Bachelor of Science
Troy University, Troy
Computer Science
Comprehensive computer science education with a strong foundation in programming, data structures, databases, and software development. Coursework emphasized analytical problem-solving, system fundamentals, and practical application of computer science concepts, supporting a transition into data analytics, data engineering, and modern web technologies.
Achievements & Honors
- ▸Honors Scholarship Recipient, Troy University
- ▸Runner-up, Troy Hackathon 2024 (Web Development)
- ▸Demonstrated strong problem-solving and full-stack development skills in competitive team environment
Featured Projects
Some of My Best Projects
Enterprise Data Warehouse & Analytics Platform
Enterprise data warehouse built using Medallion Architecture to transform ERP & CRM data into analytics-ready insights with optimized SQL models.
Certifications
Professional credentials and certifications
July 7, 2024
CERTIFICATE
for
AWS Certified Solutions Architect - Associate
Validates expertise in designing scalable, secure, and cost-efficient cloud solutions on AWS. Demonstrates strong understanding of core AWS services, architecture best practices, and cloud-native design.
Amazon Web Services
Credential ID:
0c21dccacb46490e9e4ba20bcf0b3e6d
March 20, 2024
CERTIFICATE
for
Google Data Analytics
Demonstrates practical knowledge of the end-to-end data analysis process, including data cleaning, analysis, visualization, and storytelling to support business decisions.
Coursera
Credential ID:
GCP-PCA-67890-2023
Achievements & Awards
Milestones and Recognitions
Featured Achievements
Data Warehouse Architecture & Implementation (MySQL, SQL)
GitHub
Recognized for independently designing and implementing a structured data warehouse, applying professional data modeling and optimized SQL queries to support scalable reporting.
Learn MoreRunner-up — Troy Hackathon 2024 (Web Development)
Troy University
Achieved second place in the web development track by building a full-stack application under time constraints, demonstrating strong problem-solving and teamwork.
Learn MoreAWS Certified Solutions Architect – Associate
Amazon Web Services (AWS)
Earned industry-recognized certification validating knowledge of cloud architecture, scalability, and security best practices.
Learn MoreHonors Scholarship Recipient
Troy University
Merit-based scholarship awarded for consistent academic excellence and strong performance in Computer Science coursework.
Learn MoreAll Achievements
Google Data Analytics Professional Certificate
February 2025
Completed hands-on training in data analysis, SQL, visualization, and business insights. Recognized for practical application of analytical skills.
Advanced Data Analytics & Dashboard Development (SQL, Visualization)
Microsoft PowerBI
August 2023
Demonstrated applied analytics skills by delivering professional dashboards that convert complex datasets into actionable insights for data-driven decision-making.
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