Open to opportunities

Joseph Haze

@josephhaze1

Message

I build scalable cloud data platforms and AI-driven pipelines for real-time analytics.

United States

Message

At Invisible Technologies, I build modular data platforms for finance, retail, and telecom clients, using Python, Airflow, dbt, GCP Dataflow, Pub/Sub, and Snowflake. I’ve delivered real-time pipelines processing 50M+ records per day and migrated 10TB+ of legacy data to GCP with LangChain RAG workflows for LLM-driven search and analytics.

Previously at Styleseat, I unified beauty marketplace data across bookings, payments, and user activity through Azure-based batch and real-time pipelines. I also delivered CDC analytics for cancellations and retention and helped reduce operational costs by 15% through cloud-native automation.

At Toptal, I built Spark, Kafka, Snowflake, AWS, and Databricks pipelines that reduced manual work, improved analytics access, and supported scalable platform deployments. I bring experience across aviation, healthcare, fintech, e-commerce, legal tech, and beauty and fashion.

Experience

Work history, roles, and key accomplishments

Current

Senior Al Data Engineer

Current

Invisible Technologies

Jun 2023 - Present (3 years 2 months)

Engineered modular data platforms for finance, retail, and telecom clients using Python, Airflow, and dbt, improving developer velocity by 45%. Implemented FHIR-based data models and built real-time pipelines processing 50M+ records/day with GCP Dataflow, Pub/Sub, and Snowflake.

Python Airflow DBT GCP Dataflow Pub Sub Snowflake FHIR RAG

Data Platform Engineer

Styleseat

Jan 2021 - May 2023 (2 years 4 months)

Built scalable Azure-based batch and real-time data pipelines to unify beauty marketplace data across bookings, payments, and user activity. Developed high-throughput ETL using Azure Databricks and delivered real-time analytics on cancellations and retention using CDC pipelines with Azure Synapse, Airflow, and DBT.

Azure Databricks Azure Synapse Airflow DBT CDC ETL

Data Engineer

Toptal

Jun 2017 - Nov 2020 (3 years 5 months)

Cleansed and processed messy mobile apps data using Spark streaming, Kafka, and Snowflake pipelines, reducing manual work by 20%. Designed centralized star and snowflake schemas on Apache Iceberg and integrated multiple databases into a unified platform using AWS Glue, Databricks, and S3.