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Bradley Lyman

@bradleylyman

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I build reliable cloud data, streaming, and AI platforms at massive scale.

United States

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What I'm looking for

I’m looking for a long-term senior engineering role where I can build scalable data platforms, solve complex problems, and contribute from architecture through production. I value strong engineering practices, collaborative teams, and opportunities to grow while working on cloud, data, and AI initiatives.

I've built cloud data, streaming, and AI platforms at American Express, Google, USAA, and Amazon, including pipelines processing up to 250M+ events daily and supporting low-latency financial decisioning.

At Google, I led reusable GCP ingestion frameworks and production orchestration for analytics, experimentation, and machine-learning workloads. I also partnered with ML teams on Vertex AI feature, embedding, vector-search, and RAG pipelines with permission-aware retrieval and source attribution.

I bring hands-on experience across Python, SQL, Spark, Kafka, BigQuery, Snowflake, Databricks, AWS, Azure, and GCP, with a focus on governed data products, resilient recovery patterns, and practical architecture.

Experience

Work history, roles, and key accomplishments

Senior Data Engineer

American Express

Jan 2026 - Jul 2026 (6 months)

Designed and delivered Kafka and Spark pipelines processing 20M+ daily authorization events with 99.99% availability. Automated Snowflake reconciliation using dbt and Fivetran, and established governed Databricks and Delta Lake products with Unity Catalog controls.

Kafka Spark Snowflake DBT Fivetran Databricks Delta Lake Unity Catalog Microsoft Fabric OneLake Python SQL

Senior Software Engineer

Google

Apr 2021 - Jan 2026 (4 years 9 months)

Led the design of reusable GCP ingestion frameworks for application events, PostgreSQL, APIs, Pub/Sub, and Cloud Storage, supporting analytics, experimentation, and machine-learning workloads. Standardized production orchestration with Airflow, Cloud Composer, Dagster, and Prefect, and scaled Apache Beam and Dataflow pipelines to 250M+ events daily with sub-60-second freshness and 99.9% SLA attainment.

GCP BigQuery Apache Beam Dataflow Airflow Cloud Composer Dagster Prefect DBT BigLake Iceberg Databricks Delta Lake Vertex AI RAG Vector Search PostgreSQL Pub Sub Cloud Storage

Software Engineer

USAA

Mar 2020 - Apr 2021 (1 year 1 month)

Scaled Azure Data Factory and ADLS pipelines supporting 106,000 SafePilot policies and 100,000+ daily trips. Designed trip segmentation and point-in-time policy features while correcting data quality issues, and partnered with actuarial, underwriting, and claims teams to publish curated datasets and Power BI models.