Open to opportunities

Ashlyn Rey

@ashlynrey

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Data Solutions Architect specializing in cloud-native lakehouse and streaming platforms.

United States

Message

What I'm looking for

I seek senior roles building cloud-native lakehouse and streaming platforms where I can lead architecture, mentor teams, improve governance, and optimize cloud costs.

I am an accomplished Data Solutions Architect with 12 years of experience designing cloud-native, large-scale data ecosystems across Azure, AWS, and GCP. I build high-performance Lakehouse platforms, real-time streaming pipelines, and enterprise ETL/ELT frameworks using Databricks, Snowflake, Spark, and Kafka to accelerate analytics and ML workloads.

I have modernized legacy systems into secure, event-driven, HIPAA-compliant architectures integrating FHIR, HL7, EMR/EHR, payer, and clinical sources, improving data latency, auditability, and observability. I lead engineering teams, define architectural strategy, and collaborate with executives to optimize cloud spend and governance.

My work includes producing scalable APIs, microservices, and curated data marts, creating automated quality, lineage, and governance frameworks, and delivering measurable improvements in reliability and cost. I am recognized for technical leadership, problem solving, and designing future-ready data environments for healthcare, finance, and telecom.

Experience

Work history, roles, and key accomplishments

Current

Data Solutions Architect

Current

CoEnterprise

Jul 2022 - Present (3 years 5 months)

Designed and delivered large-scale cloud-native Lakehouse platforms across Azure and AWS, enabling real-time clinical, financial, and operational insights and reducing onboarding time for new data products by over 20%.

Databricks Snowflake Kafka Azure Data Governance Lakehouse

Lead Data Engineer

Fipsar Inc

Dec 2018 - Jun 2022 (3 years 6 months)

Led migration of legacy ETL into Snowflake and modernized batch workflows into Delta Lake near-real-time pipelines, improving analytical efficiency by over 30% and achieving 99%+ pipeline reliability.

Azure Data Factory Snowflake Delta Lake Spark Great Expectations ETL

Big Data Engineer

ThirdEye Data

Apr 2015 - Nov 2018 (3 years 7 months)

Developed fault-tolerant Spark and Kafka-based distributed pipelines to process multi-terabyte datasets, improving processing speed and cluster utilization while enabling reusable datasets for ML and analytics.

Apache Spark Kafka Hive Hadoop Airflow Kubernetes Performance Tuning Distributed Systems

Data Platform Engineer

D2i

Jan 2013 - Mar 2015 (2 years 2 months)

Supported ETL and data processing pipelines using SQL and Python to deliver analytics-ready datasets, optimized queries and storage strategies to improve query performance and platform stability.