Lead Engineer Resume Example

Lead Software Engineer · QuantEdge Solutions

Seattle, WA · 2022 - Present

• Led a team of 5 engineers in the design and implementation of a new ultra-low latency market data pipeline, reducing end-to-end latency by 35% (from 50us to 32.5us) across major exchanges.
• Architected and deployed a highly concurrent order management system (OMS) capable of processing over 100,000 orders per second with 99.999% uptime, utilizing C++ and Kafka.
• Mentored junior and mid-level engineers, fostering a culture of technical excellence and best practices in critical system development.
• Optimized existing trade execution algorithms, achieving a 12% improvement in fill rates and a 7% reduction in slippage through code refactoring and kernel-level tuning.
• Developed and maintained critical monitoring and alerting tools for production systems, leading to a 40% faster incident response time.

Senior Software Engineer · Nexus Financial Group

New York, NY · 2018 - 2022

• Designed and implemented a distributed portfolio risk calculation engine in Python, processing over 1TB of market data daily and reducing computation time by 60%.
• Developed high-throughput APIs for internal trading desks, handling over 5,000 requests per second with average response times under 10ms.
• Led the migration of critical financial reporting services to AWS, resulting in a 25% reduction in infrastructure costs and enhanced scalability.
• Collaborated with quantitative researchers to integrate new statistical models into the trading platform, improving predictive accuracy by 8%.

Software Engineer · Apex Market Data

Boston, MA · 2015 - 2018

• Contributed to the development of a real-time financial data aggregation platform, processing data from 50+ sources with an average ingestion latency of 200ms.
• Implemented data quality checks and validation routines that reduced data errors by 15%, ensuring high integrity for downstream systems.
• Developed client-facing APIs for market data access, handling up to 2,000 concurrent connections.
• Participated in an on-call rotation, providing support for critical production systems and resolving issues within established SLAs.

Master of Science in Computer Science · University of Washington

Seattle, WA · 2014 - 2015

• Specialized in Distributed Systems, High-Performance Computing, and Quantitative Finance.
• Thesis: "Optimizing Micro-latency for Algorithmic Trading Architectures using FPGA Acceleration."
• GPA: 3.9/4.0

Bachelor of Science in Computer Science · University of Washington

Seattle, WA · 2010 - 2014

• Graduated Magna Cum Laude.
• Relevant Coursework: Data Structures, Operating Systems, Computer Networks, Discrete Mathematics.
• GPA: 3.8/4.0

Lead Software Engineer · Workday

Austin, TX · 2022 - Present

• Led a team of 5 engineers in designing and implementing a new microservices-based reporting platform, reducing report generation time by 30% for 100K+ enterprise users.
• Architected and deployed a highly available data synchronization service using Kafka and Kubernetes, improving data consistency across 5 critical systems by 99.9%.
• Mentored junior and mid-level engineers, resulting in a 25% increase in team code quality and a 15% reduction in production incident rates over 12 months.
• Drove adoption of new technologies like Apache Cassandra for scalable storage, optimizing query performance by 40% and cutting infrastructure costs by 18%.
• Collaborated cross-functionally with product managers and SRE teams to define technical roadmaps, contributing to a 20% faster delivery of key product features.

Software Engineer, Data Platforms · Indeed

Austin, TX · 2020 - 2022

• Developed and maintained scalable data pipelines using Apache Spark and Scala, processing over 10TB of job applicant data daily with 99.8% uptime.
• Designed and implemented RESTful APIs for internal data consumption, reducing data access latency by 150ms for downstream applications.
• Contributed to the modernization of legacy data infrastructure, migrating critical workflows to AWS EMR, which reduced operational costs by 20% annually.
• Implemented robust monitoring and alerting for data pipelines using Prometheus and Grafana, proactively identifying and resolving issues before impacting users.

Senior Data Scientist · Accenture

Atlanta, GA · 2015 - 2018

• Developed and deployed machine learning models in Python, improving predictive accuracy for client's customer churn by 15% and increasing retention by 5%.
• Automated data extraction and transformation processes using SQL and Spark, reducing manual data preparation time by 40 hours per week for a team of 10 analysts.
• Presented actionable insights from complex datasets to executive stakeholders, influencing strategic decisions that resulted in a 10% increase in marketing campaign ROI.

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

Austin, TX · 2018 - 2020

• Specialization in Distributed Systems and Machine Learning Engineering.
• Thesis: "Scalable Real-time Anomaly Detection using Apache Flink and Kafka," achieving 92% detection accuracy.
• Coursework: Advanced Algorithms, Cloud Computing, Distributed Databases, Machine Learning Systems.

Bachelor of Science in Applied Mathematics · Georgia Institute of Technology

Atlanta, GA · 2014 - 2018

• Graduated with High Honors, GPA: 3.8/4.0.
• Relevant Coursework: Probability and Statistics, Linear Algebra, Differential Equations, Data Structures.
• Awarded Dean's List for 6 consecutive semesters.