Databricks Developer Resume Example

Senior Databricks Engineer · Ally Financial

Charlotte, NC · 2023 - Present

• Architected and implemented real-time data pipelines on Databricks, processing over 10TB of streaming financial transactions daily, reducing fraud detection latency by 40% for critical alerts.
• Developed and optimized PySpark jobs for a core anti-money laundering (AML) system, improving data processing efficiency by 30% and ensuring compliance with stringent regulatory standards.
• Collaborated with data science teams to deploy and operationalize 5+ machine learning models for credit risk assessment and customer churn prediction, directly contributing to a 15% reduction in loan defaults.
• Managed and fine-tuned Databricks Unity Catalog for enterprise-wide data governance across 50+ financial datasets, enhancing data security and auditability for quarterly regulatory reporting.

Databricks Engineer · Fiserv

Atlanta, GA · 2021 - 2022

• Designed and implemented scalable ETL processes using Databricks and Spark for ingesting diverse financial market data, handling up to 5TB of data weekly from 20+ sources.
• Migrated legacy on-premise data warehousing solutions to a cloud-native Databricks Lakehouse architecture, resulting in a 25% cost reduction and 50% improvement in ad-hoc query performance.
• Automated data quality checks and validation frameworks for core financial datasets, reducing data errors by 20% and improving data reliability for downstream business intelligence initiatives.

Master of Science in Analytics (MSAN) · Georgia Institute of Technology

Atlanta, GA · 2019 - 2021

• GPA: 3.9/4.0
• Relevant Coursework: Big Data Systems, Machine Learning, Statistical Modeling, Data Visualization, Data Mining
• Thesis: "Optimizing Real-time Fraud Detection using Stream Processing and Ensemble Learning"

Bachelor of Science in Computer Science · University of Florida

Gainesville, FL · 2015 - 2019

• GPA: 3.8/4.0, Magna Cum Laude
• Relevant Coursework: Data Structures and Algorithms, Database Systems, Software Engineering, Discrete Mathematics

Lead Databricks Developer · Dell Technologies

Austin, TX · 2024 - Present

• Engineered and deployed a critical data ingestion pipeline for IoT device telemetry using Databricks and Delta Lake, processing over 10TB of raw data daily and reducing latency by 40% for real-time analytics.
• Led the migration of on-premise data warehouses to Databricks Lakehouse Platform on AWS, achieving a 25% reduction in operational costs and improving data query performance by 3x for key business intelligence dashboards.
• Developed and maintained a robust CI/CD pipeline for Databricks notebooks and jobs using Azure DevOps, increasing deployment frequency by 50% and ensuring code quality through automated testing frameworks.
• Mentored a team of 3 junior data engineers on Databricks best practices, PySpark optimization, and cloud-native data architecture patterns, significantly enhancing team productivity and skill development.

Data Engineer · Capital One

Plano, TX · 2021 - 2023

• Designed and implemented ETL processes using PySpark on Databricks for financial transaction data, resulting in a 30% improvement in data loading efficiency for reporting systems.
• Collaborated with data scientists to optimize Spark jobs for machine learning model training, reducing execution time by an average of 15% for credit risk assessment models.
• Developed custom UDFs in PySpark to standardize and cleanse disparate data sources, improving data quality metrics by 20% and reducing manual data preparation efforts.
• Managed and monitored Databricks clusters and jobs, ensuring high availability and optimal performance for critical business operations, leading to 99.9% uptime.

Business Intelligence Analyst · Accenture

Dallas, TX · 2020 - 2021

• Developed and maintained interactive dashboards and reports using Tableau and Power BI for key clients, providing insights that led to a 10% increase in client revenue forecasts accuracy.
• Performed complex SQL queries and data analysis on large datasets to identify business trends and inefficiencies, contributing to a 5% optimization in operational costs for a retail client.
• Automated routine data extraction and reporting tasks using Python scripts, saving approximately 15 hours per week in manual effort for the analytics team.
• Collaborated with cross-functional teams to define data requirements and translate business needs into technical specifications for data warehousing projects.

Master of Science in Data Science · University of Texas at Austin

Austin, TX · 2018 - 2020

• Thesis: "Optimizing Large-Scale Data Processing for Real-time Analytics using Apache Spark on Cloud Platforms"
• Relevant Coursework: Advanced Machine Learning, Big Data Systems, Cloud Computing for Data Science, Data Visualization
• GPA: 3.9/4.0

Bachelor of Science in Business Analytics · Texas A&M University

College Station, TX · 2014 - 2018

• Graduated Magna Cum Laude
• Relevant Coursework: Statistical Modeling, Database Management, Data Mining, Business Intelligence Systems
• GPA: 3.8/4.0