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Taylor Pentz

@taylorpentz1

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Experienced Senior Data Engineer specializing in scalable data solutions.

United States

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What I'm looking for

I am looking for a role that fosters innovation and allows me to leverage my data engineering skills while promoting a collaborative and growth-oriented company culture.

I am a Senior Data Engineer with over 10 years of experience in building scalable data pipelines and optimizing ETL workflows. My expertise lies in utilizing Python and its frameworks, such as Pandas and PySpark, to process large datasets and integrate with cloud platforms like AWS, Google Cloud, and Azure. I have a proven track record of designing data models and ensuring data quality, which has significantly improved data accessibility and performance for analytical workloads.

Throughout my career, I have architected and executed complex data workflows, leading to a 30% enhancement in data processing efficiency. I have successfully developed and maintained robust backend microservices and RESTful APIs, enabling high-performance application architectures. My commitment to data governance and security has ensured compliance with organizational policies while safeguarding data integrity.

Experience

Work history, roles, and key accomplishments

Senior Lead Data Engineer

InnoS

Apr 2022 - Present (3 years 2 months)

Architected and executed scalable ETL pipelines and complex data workflows leveraging Python, Apache Airflow, and cloud-native services (AWS Glue, Azure Data Factory), resulting in a 30% enhancement in data processing efficiency. Developed and maintained robust backend microservices and RESTful APIs utilizing Python frameworks such as Django, Flask, and FastAPI, enabling modular, and high-performa

Python Apache Airflow AWS Glue Azure Data Factory Django Flask fastAPI PostgreSQL MongoDB Celery GitHub Actions Jenkins React Next.js

Senior Data Engineer

Modis

Mar 2020 - Present (5 years 3 months)

Spearheaded the design, development, and automation of scalable ETL pipelines across both Big Data and Business Intelligence (BI) platforms, optimizing data integration and ensuring seamless workflows. Led the successful migration of ETL jobs and related services from legacy BI systems to advanced Big Data interfaces, improving data processing efficiency and scalability. Architected and implemente

ETL Big Data Business Intelligence Apache NiFi Shell Scripting Python Apache Airflow SQL Data Warehousing Data Governance

Senior Data Engineer

IBM

Aug 2015 - Present (9 years 10 months)

Engineered and optimized scalable data pipelines and ETL workflows using Python and relevant data processing frameworks, improving data integration efficiency across multiple platforms. Developed robust, automated web scraping tools with libraries such as BeautifulSoup, Scrapy, and Selenium to extract, clean, and transform large volumes of web data with high accuracy. Designed and implemented high

Python ETL BeautifulSoup Scrapy Selenium Hadoop Spark Kafka RESTful APIs AWS Azure S3 Lambda Azure Data Factory Docker Kubernetes Agile

Education

Degrees, certifications, and relevant coursework

Florida State University

Master of Science (M.S.), Engineering/Industrial Management

Completed a Master of Science degree in Engineering/Industrial Management. Focused on advanced topics relevant to industrial operations and management.