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I'm Alee Ash, a data solutions architect and senior data engineer based in Syracuse, NY. With over a decade of experience, I design and scale robust data systems, build end-to-end pipelines, and drive cloud migrations across AWS, Azure, and GCP to support analytics and product teams. I collaborate with data scientists, analysts, and engineers to ensure data is accessible, accurate, and actionable. My toolkit includes Spark, Kafka, Airflow, dbt, Snowflake, and Terraform, with hands-on experience deploying platforms on multiple clouds and implementing CI/CD, observability, and governance to deliver fast, reliable, and maintainable data solutions.…I'm Alee Ash, a data solutions architect and senior data engineer based in Syracuse, NY. With over a decade of experience, I design and scale robust data systems, build end-to-end pipelines, and drive cloud migrations across AWS, Azure, and GCP to support analytics and product teams. I collaborate with data scientists, analysts, and engineers to ensure data is accessible, accurate, and actionable. My toolkit includes Spark, Kafka, Airflow, dbt, Snowflake, and Terraform, with hands-on experience deploying platforms on multiple clouds and implementing CI/CD, observability, and governance to deliver fast, reliable, and maintainable data solutions.

Alee Ash

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I'm Alee Ash, a data solutions architect and senior data engineer based in Syracuse, NY. With over a decade of experience, I design and scale robust data systems, build end-to-end pipelines, and drive cloud migrations across AWS, Azure, and GCP to support analytics and product teams. I collaborate with data scientists, analysts, and engineers to ensure data is accessible, accurate, and actionable. My toolkit includes Spark, Kafka, Airflow, dbt, Snowflake, and Terraform, with hands-on experience deploying platforms on multiple clouds and implementing CI/CD, observability, and governance to deliver fast, reliable, and maintainable data solutions.…I'm Alee Ash, a data solutions architect and senior data engineer based in Syracuse, NY. With over a decade of experience, I design and scale robust data systems, build end-to-end pipelines, and drive cloud migrations across AWS, Azure, and GCP to support analytics and product teams. I collaborate with data scientists, analysts, and engineers to ensure data is accessible, accurate, and actionable. My toolkit includes Spark, Kafka, Airflow, dbt, Snowflake, and Terraform, with hands-on experience deploying platforms on multiple clouds and implementing CI/CD, observability, and governance to deliver fast, reliable, and maintainable data solutions.

Available to hire

I’m Alee Ash, a data solutions architect and senior data engineer based in Syracuse, NY. With over a decade of experience, I design and scale robust data systems, build end-to-end pipelines, and drive cloud migrations across AWS, Azure, and GCP to support analytics and product teams.

I collaborate with data scientists, analysts, and engineers to ensure data is accessible, accurate, and actionable. My toolkit includes Spark, Kafka, Airflow, dbt, Snowflake, and Terraform, with hands-on experience deploying platforms on multiple clouds and implementing CI/CD, observability, and governance to deliver fast, reliable, and maintainable data solutions.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Lead Data Engineer at CorroHealth

June 1, 2021 - Present

Leading architecture and deployment of end-to-end data platforms leveraging AWS (Glue, Redshift, S3, Lambda), GCP (BigQuery, Dataflow), and Azure (Synapse, Data Lake) to handle both streaming and batch data at scale. Designing and orchestrating complex ETL/ELT pipelines using Apache Airflow, dbt, and Apache Beam, integrating structured and semi-structured data across diverse systems. Managing real-time data ingestion with Apache Kafka, Amazon Kinesis, and Flink, enabling sub-second analytics and operational dashboards for internal stakeholders. Driving MLOps initiatives by productionizing ML models using Kubeflow, MLflow, and Docker/Kubernetes, with deployment pipelines built on CI/CD workflows in Jenkins and GitHub Actions. Implementing Infrastructure as Code (IaC) with Terraform and Helm, and standardizing environment management across cloud providers and Kubernetes clusters. Enforcing robust data governance and compliance via tools like Apache Atlas, DataHub, and Great Expectations,

Senior Data Engineer at Analytics8

August 1, 2018 - May 1, 2021

Architected and maintained scalable ETL pipelines using Airflow and AWS Glue to process and normalize advertising data across multiple sources. Led migration of legacy data systems to a cloud-native stack on AWS (S3, Redshift, Lambda), improving performance and reducing operational overhead. Collaborated with cross-functional teams to design data models and warehouse schemas in Redshift and Snowflake, enabling faster analytics and reporting. Integrated Kafka for real-time data streaming and built robust ingestion pipelines with Python and Spark for time-sensitive ad delivery insights. Implemented CI/CD workflows using GitHub Actions and Terraform to automate deployments and infrastructure provisioning. Ensured data quality and observability through automated testing, monitoring (Datadog, CloudWatch), and lineage tracking using DataHub.

Data Engineer at Etleap

June 1, 2014 - July 1, 2018

Joined an early-stage startup team where I worked closely with engineers to support the design and implementation of ETL pipelines, helping move data from various sources into centralized systems for analysis. Wrote and maintained Python and SQL scripts to perform data cleaning, transformation, and enrichment tasks that improved the quality and usability of data for downstream reporting. Gained hands-on experience with orchestration tools like Apache Airflow and AWS Glue by setting up simple DAGs and understanding how to schedule, monitor, and rerun jobs when needed. Assisted in identifying and resolving pipeline failures by checking logs, validating data outputs, and shadowing senior engineers to better understand common reliability issues. Worked within cloud-based environments using services like Amazon S3 for storage and Redshift for querying structured data, learning how cloud infrastructure supports scalable analytics. Contributed to internal documentation and knowledge sharing,