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Ryan User

@ryanuser7

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Senior Data Engineer with expertise in scalable data-driven systems.

United States

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What I'm looking for

I am seeking a role that fosters innovation and collaboration, where I can leverage my data engineering skills to drive impactful solutions and contribute to team growth.

As a Senior Data Engineer with over 10 years of experience, I have a proven track record in building scalable, data-driven systems across various industries, including healthcare, e-commerce, and finance. My expertise lies in designing and optimizing real-time data pipelines and cloud-native solutions, integrating AI/ML models for predictive analytics and decision support. I am passionate about solving complex problems with data and work closely with cross-functional teams to develop efficient, automated workflows.

Throughout my career, I have engineered data-driven healthcare solutions that significantly improved document processing efficiency and reduced processing times. I have built and optimized real-time data pipelines, developed scalable data repositories, and implemented automated data quality checks, all of which have enhanced data accessibility and accuracy. My commitment to continuous learning and growth has also led me to mentor junior data engineers, fostering a culture of knowledge sharing and best practices within my teams.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

Prime Healthcare

Mar 2021 - Present (4 years 4 months)

Engineered data-driven healthcare solutions using Python, Scala, TensorFlow, Google Cloud AI, and Databricks, improving document processing efficiency by 75% and reducing processing time by 30%, enabling clinicians to access critical data faster. Built and optimized real-time data pipelines with Python, Apache Kafka, Google Cloud Dataflow, and Databricks, improving data integration efficiency by 6

Data Engineer

Apple

Mar 2019 - Feb 2021 (1 year 11 months)

Designed and implemented scalable ETL pipelines using Python, Spark, and AWS to process and integrate large datasets for e-commerce and finance analytics, reducing data processing times by 40%. Developed and deployed real-time analytics dashboards in Power BI and Tableau, providing key insights into customer behavior and financial transactions, which led to a 15% increase in revenue generation thr

Python Spark AWS Power BI Tableau Keras TensorFlow Apache Kafka AWS Kinesis AWS S3 scikit learn Apache Airflow GDPR PCI DSS AWS RedShift AWS Cloudwatch azure monitor Azure Data Factory AWS Glue Azure DevOps Docker CI CD

Data Engineer

Databricks

Jan 2017 - Feb 2019 (2 years 1 month)

Developed ETL pipelines using Apache Spark and Databricks, enabling clients in e-commerce and finance to process large volumes of data efficiently and reduce processing time by 40%. Built and maintained real-time data processing pipelines using Apache Kafka, AWS Kinesis, and Azure Event Hubs, ensuring smooth data flow and low-latency event processing.

Apache Spark Databricks Apache Kafka AWS Kinesis Azure Event Hubs AWS S3 TensorFlow Apache Airflow AWS Glue Power BI Tableau Delta Lake Azure Data Factory

Software Developer

OpenArc, LLC

Aug 2014 - Dec 2016 (2 years 4 months)

Developed and maintained backend services using Java, Spring Boot, and RESTful APIs, improving system efficiency and ensuring scalability for client-facing applications. Built and integrated data processing pipelines using Python and Spark to streamline the transformation and loading of data for reporting purposes.

Java Spring Boot RESTful APIs Python Spark PostgreSQL MySQL Junit Mockito SOAP

Education

Degrees, certifications, and relevant coursework

University of Pittsburgh

Bachelor of Science, Computer Engineering

Studied Computer Engineering, gaining foundational knowledge in computer science and engineering principles. Focused on developing skills in system design, software development, and problem-solving.