Open to opportunities

Jeff Akin

@jeffakin

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Lead Data Engineer specializing in cloud-native, scalable data platforms.

United States

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What I'm looking for

I seek senior/lead roles building cloud-native data platforms, focusing on scalable ETL/ELT, data governance, compliance, and mentoring teams in a collaborative, security-conscious environment.

I am a Lead Data Engineer with 9+ years designing scalable cloud data platforms and high-performance ETL/ELT pipelines across healthcare, finance, and manufacturing. I have built serverless ingestion pipelines processing 500M+ daily events, modernized legacy systems to Snowflake and cloud warehouses, and led teams to deliver enterprise-grade, secure data solutions.

My expertise spans Spark, Kafka, Flink, Airflow, dbt, Snowflake, BigQuery, Redshift, Terraform, and Kubernetes, with strong focus on data modeling, governance, HIPAA/GDPR compliance, real-time streaming, MLOps, and analytics enablement. I mentor engineers, automate data quality and observability, and drive cloud-native migrations that reduce cost and improve reliability.

Experience

Work history, roles, and key accomplishments

Current

Lead Data Engineer

Current

Lark Health

Jan 2023 - Present (2 years 11 months)

Designed and led enterprise cloud data architectures across AWS and Azure, building cloud-native ETL/ELT pipelines and Snowflake data models to support healthcare analytics and regulatory reporting with high reliability and compliance.

Snowflake Airflow Kafka AWS Azure ETL Data Modeling Terraform Data Pipelines

Senior Data Engineer

EE-Medix

Aug 2019 - Dec 2022 (3 years 4 months)

Architected a centralized financial analytics platform on Snowflake, migrated legacy workloads to modern warehouses, and built batch and streaming pipelines to improve reliability and reporting accuracy.

Snowflake Azure Synapse BigQuery Kafka Streams Flink DBT Power BI Data Governance

ETL & Data Warehouse Engineer

Azumo

Jun 2017 - Jul 2019 (2 years 1 month)

Engineered large-scale IoT and streaming data processing workflows using Hadoop ecosystem and real-time platforms, and developed ML-driven anomaly detection and predictive dashboards.