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BennyM User

@bennymuser

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Senior Data Engineer building scalable ETL/ELT and real-time, AI-ready data platforms.

United States

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What I'm looking for

I’m looking to build reliable, scalable, AI-ready data platforms—leveraging lakehouse architectures, DataOps, and real-time analytics to help teams make data-driven decisions at scale while improving performance and cost efficiency.

I’m a Senior Data Engineer with 7+ years of experience designing scalable ETL/ELT pipelines, real-time streaming systems, and cloud-native data platforms. I specialize in Python, SQL, PySpark, and modern data stack technologies like Snowflake, Databricks, Kafka, and Airflow.

I’ve built and optimized high-volume pipelines processing 2TB+ daily—improving pipeline efficiency by up to 35%, reducing query latency by 40%, and cutting infrastructure costs by 25%. I also bring DataOps and reliability practices using dbt, CI/CD, Docker, Kubernetes, and Terraform, and I enjoy mentoring junior engineers to accelerate delivery.

Experience

Work history, roles, and key accomplishments

Current

Senior Data Engineer

Current

USTechnologyWorld

Mar 2023 - Present (3 years 3 months)

Designed and optimized scalable Python/PySpark ETL/ELT pipelines processing 2TB+ data daily, improving pipeline efficiency by 35%. Migrated on-prem data warehouse to Snowflake, reducing query latency by 40% and infrastructure costs by 25%, and built Kafka/Spark streaming pipelines enabling sub-second dashboard availability.

Python Pyspark SQL Snowflake Kafka Apache Airflow DBT Data Modeling Data Quality

Data Engineer

QuartzQuery

Feb 2021 - Mar 2023 (2 years 1 month)

Developed and maintained ETL pipelines processing 500GB+ of structured and unstructured data using SQL and Python. Built AWS-based data warehouse solutions (S3/Redshift/Glue) improving data accessibility by 40%, automated workflows with Airflow (-70% manual intervention), and optimized SQL performance by 50%.

SQL Python AWS S3 Amazon Redshift AWS Glue Apache Airflow Kafka Data Warehousing Performance Tuning ETL

Junior Data Engineer

Dataiku

Sep 2018 - Feb 2021 (2 years 5 months)

Assisted in building Python/SQL ETL pipelines processing 100GB+ data daily, improving data accuracy by 25% through data cleaning and transformations. Monitored and debugged pipelines to reduce job failures by 30% and supported BI reporting requirements with optimized SQL.

Python SQL ETL Data Cleaning data transformation Data Modeling Debugging BI Reporting