Data Pipeline Engineer Resume Example

Senior Data Pipeline Engineer · Indeed

Austin, TX · 2022 - Present

• Led the design and implementation of a new real-time data ingestion pipeline using Kafka and Spark Streaming, reducing data latency by 40% and supporting 10+ downstream analytics applications.
• Optimized existing ETL processes in AWS Glue, decreasing daily processing time by 25% and cutting operational costs by $15,000 annually.
• Mentored a team of 3 junior data engineers, improving code quality and deployment efficiency by 30% through best practices and code reviews.
• Developed and maintained data quality monitoring dashboards using Grafana and Prometheus, proactively identifying and resolving data anomalies for over 5TB of daily data.

Data Engineer · BigCommerce

Austin, TX · 2019 - 2022

• Built and maintained scalable data pipelines using Python, Airflow, and Snowflake, processing over 10TB of transactional data monthly for business intelligence reporting.
• Implemented robust data validation and error handling mechanisms, reducing data pipeline failures by 18% and improving data accuracy by 99.5%.
• Collaborated with product and analytics teams to gather requirements and deliver data solutions, resulting in a 10% increase in critical metric visibility.
• Automated deployment of data assets using CI/CD pipelines, accelerating delivery cycles by 20%.

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

Austin, TX · 2017 - 2019

• Completed thesis on real-time data streaming architectures, achieving a 3.9 GPA.
• Awarded 'Dean's List' for academic excellence in Fall 2018 and Spring 2019.
• Developed a machine learning pipeline for predictive analytics, improving model accuracy by 15%.

Bachelor of Science in Computer Science · Texas A&M University

College Station, TX · 2013 - 2017

• Graduated Cum Laude with a 3.7 GPA.
• Active member of the ACM student chapter, leading workshops on Python for data analysis.
• Developed a data visualization tool for faculty research projects.

Senior Data Pipeline Engineer · Zillow Group

Seattle, WA · 2022 - Present

• Designed and implemented real-time data pipelines using Apache Kafka and Flink, processing over 10TB of property listing updates daily with 99.9% uptime, reducing data latency by 60%.
• Developed and maintained ETL processes for machine learning model training data, improving data freshness for pricing algorithms by 40% and increasing model accuracy by 5%.
• Automated data quality checks and anomaly detection systems for critical data feeds, preventing 15+ potential data integrity issues per month.
• Mentored junior engineers on best practices for scalable data pipeline development and cloud infrastructure management, contributing to a 25% improvement in team project delivery speed.

Data Pipeline Engineer · Redfin

Seattle, WA · 2018 - 2022

• Built and optimized batch data pipelines using Apache Spark on AWS EMR, reducing daily ETL job run times by an average of 35% for property data ingestion.
• Managed and scaled a data warehouse on AWS Redshift, processing over 5TB of historical real estate transaction data, supporting analytical reporting for 500+ internal users.
• Developed custom Airflow DAGs for orchestrating complex data workflows, improving job success rates from 90% to 98% through robust error handling and monitoring.
• Collaborated with data scientists to prepare and integrate new data sources into the data lake, enabling the development of 3 new predictive analytics features.

Master of Science in Computer Science · University of Washington

Seattle, WA · 2016 - 2018

• Specialization in Distributed Systems and Data Engineering.
• GPA: 3.9/4.0.

Bachelor of Science in Computer Engineering · University of California, San Diego

La Jolla, CA · 2012 - 2016

• Graduated Magna Cum Laude.
• Relevant coursework: Data Structures, Algorithms, Database Systems, Operating Systems.