Spencer Carmical
@spencercarmical2
Senior Data Engineer specializing in scalable pipelines, cloud data platforms.
What I'm looking for
I am a Senior Data Engineer with over nine years building scalable ETL pipelines, cloud-native data platforms, and analytics warehouses to enable data-driven decisions. I specialize in Python, Spark, Airflow, Snowflake, Redshift, and cloud solutions (AWS, GCP, Azure), and I deliver robust, compliant systems for high-volume, regulated environments.
I have led real-time architectures using Kafka and dbt, implemented automated validation and CI/CD practices, and deployed machine learning models into production that improved outcomes such as recovery effectiveness and churn detection. I prioritize data governance, security, and cross-functional collaboration to drive measurable business impact while maintaining operational reliability.
Experience
Work history, roles, and key accomplishments
Senior Data & Python Engineer
Attention
Jan 2022 - May 2025 (3 years 4 months)
Architected and managed scalable ETL pipelines and real-time data infrastructure (Kafka, Snowflake, dbt) to support collections and payments reporting, reducing manual work by 80% and improving recovery effectiveness by 12%.
Senior Data Engineer
Secure Haven LLC
May 2020 - Jan 2022 (1 year 8 months)
Built a cloud-native data platform and Snowflake warehouse with ETL (Airflow, dbt) and ML pipelines that reduced reporting latency by 75% and enabled churn/failure prediction and productionized models.
Senior Data & Scraping Engineer
Altimize
Aug 2016 - Mar 2020 (3 years 7 months)
Designed and optimized ETL and real-time streaming pipelines for healthcare and financial data, implemented web scraping and APIs, and led cloud migrations to meet HIPAA/PCI-DSS compliance.
Education
Degrees, certifications, and relevant coursework
University of Arkansas
Bachelor's Degree, Computer Engineering
2012 - 2016
Completed a Bachelor's Degree in Computer Engineering at the University of Arkansas, focusing on computing fundamentals and engineering principles.
Tech stack
Software and tools used professionally
Amazon Redshift
Azure Synapse
Apache Spark
AWS Glue
Metabase
Amazon S3
GitHub
Kubernetes
Jenkins
GitHub Actions
Pandas
dbt
PostgreSQL
MongoDB
Hadoop
Shopify
Gmail
Django
.NET
Databricks
Java
AWS CloudTrail
scikit-learn
Kafka
Apache NiFi
FastAPI
asyncio
AWS Lambda
SendGrid
Twilio
BeautifulSoup
Airflow
s3-lambda
SQL
Great Expectations
Availability
Location
Authorized to work in
Job categories
Skills
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