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Patrick Browne\\
Data Leader \& Architect

719.338.4035 | Colorado\\
patrickbrowne@outlook.com | pbrowne.net

LinkedIn

PROFESSIONAL SUMMARY

Seasoned big data leader, engineer, and architect with over 15 years of experience. Prioritizes a progressive,\\
systematic, and results driven approach to AI. Excels at solving large-scale technical and strategic problems and\\
thrives in fast-paced environments with limited resources. A data-driven decision maker who constantly seeks\\
out innovative and disruptive opportunities, values candid feedback, and encourages lateral thinking among\\
colleagues. Emphasis on continuous learning and mentoring within a highly collaborative environment.

SKILLS

\textbullet{}  AI/LLM/ML Development \& Implementation\\
\textbullet{}  Enterprise Data Platform Architecture\\
\textbullet{}  Revenue Forecasting \& Cost Optimization\\
\textbullet{}  Data Org Management and Structuring

\textbullet{}  Product Roadmapping and Development\\
\textbullet{}  Project Management \& Agile Leadership\\
\textbullet{}  Data Governance Systems\\
\textbullet{}  Hybrid \& Native Cloud Best Practices

WORK HISTORY

Sovrn Holdings Inc. - Boulder, CO 2016 - Current\\
Senior Manager, Data Engineering (2024 - Present)

\textbullet{}  Transforming development workﬂows by leveraging agentic AI, MCP, and LLM across multiple teams\\
\textbullet{}  Leading a multi-team Data Engineering org, encompassing product, platform, and internal teams\\
\textbullet{}  Driving cross-organizational product initiatives to develop industry leading oﬀerings leveraging AI\\
\textbullet{}  Forecasting revenue and operational cost, including continual cost optimizations\\
\textbullet{}  Serving as a technical leader for Data Governance and Compliance\\
\textbullet{}  Mentoring managerial staﬀ and multiple teams with diverse objectives under Data Engineering\\
\textbullet{}  Serving as the key contact for internal and external stakeholders

Manager \& Staﬀ Engineer (2022 - 2024)

\textbullet{}  Owned of multiple observability platforms for AI/LLM and Big Data/Data Analytics workﬂows\\
\textbullet{}  Architected and administered an AWS zero-trust multi-tenant organization\\
\textbullet{}  Designed a streaming backend capable of handling 20GB/s, processing over 250 billion records daily\\
\textbullet{}  Managed internal and external batch processing ETLs using Spark\\
\textbullet{}  Mentored and led projects, ensuring documentation, process improvement, quality standards, and

on-time delivery

\textbullet{}  Led the support for frontend, backend, and middle-ware cloud migration from on-prem to AWS

Senior Software Engineer (2020 - 2022)

\textbullet{}  Architect, and mentor for serverless, containerized, and big data storage, ingress, and egress\\
\textbullet{}  Championed and mentored junior team members in best practices

Software Engineer II (2018 - 2020)

\textbullet{}  Key contributor in AWS migration and development of Data Science processes\\
\textbullet{}  Administered cloud and on-prem infrastructure for streaming and big data

Senior Software Developer in Test (2016 - 2018)

\textbullet{}  Test automation lead for a Data Platform team of 9 developers\\
\textbullet{}  Designed and maintained ephemeral system and integration test suites

Dish Networks - Denver, CO 2015 - 2016\\
QA Test Engineer II

\textbullet{}  Lead Quality Assurance for the Data Architecture team\\
\textbullet{}  Designed and maintained front-end Java-based test automation framework

Drobo/Connected Data - Santa Clara, CA 2012 - 2015\\
QA Test Engineer

\textbullet{}  Lead tester for the launch of the Transporter private cloud storage device\\
\textbullet{}  Lead tester for Drobo storage devices, both enterprise and commercial

KEY PROJECTS

Leadership

\textbullet{}  Organizational restructuring and alignment for backend and data departments\\
\textbullet{}  Extensive experience in managing multi-team and geographically diverse groups\\
\textbullet{}  Hands on inﬂuence on go-to-market strategy, technical implementation, and product roadmap\\
\textbullet{}  Led a product-driven team for data wholesale oﬀerings, managing 9+ oﬀerings with a 55+\% gross proﬁt

margin and generating \$12M in annual revenue

\textbullet{}  Led Data Platform teams ingestioning, governing, and storing over 4PB of data per week\\
\textbullet{}  Led Data Science, Data Analytics, and other “data-centric” teams\\
\textbullet{}  Experience in contract negotiation and strategic forecasting using metrics-driven industry research\\
\textbullet{}  ROI evaluation systems across products in AWS, Databricks, Snowﬂake, and other platforms\\
\textbullet{}  Served as the point of contact for government and consumer data compliance

AI/LLM/ML

\textbullet{}  End to end AI Agent workﬂow from JIRA ticket to PR and production deploy.\\
\textbullet{}  Organization wide agent Context and MCP layer with dreaming compaction and Claude plugin\\
\textbullet{}  Vectorized RAG implementation of canonical ID segments with entity resolution and autodidactic

reinforcement

\textbullet{}  Architect for an AI LLM powered web content categorizer for audience and deal packaging for adtech\\
\textbullet{}  Engineering lead for lookalike audience modeling, unifying disparate datasets

Project Management

\textbullet{}  Led large-scale migrations and refactor eﬀorts across the company, delivering projects on time and

within budget

\textbullet{}  Evolved the full-tech stack of the adtech backend, serving both internal and external stakeholders\\
\textbullet{}  Migrated of 60 node on-prem data lake and legacy data analytics architecture into native cloud system\\
\textbullet{} 

Implemented ground up tech adoption for both Snowﬂake and Databricks

Data Governance/Admin

\textbullet{} 

Implemented OPA and a single service layer to unify access to multiple products lines

\textbullet{}  Created a canonical ID system creation and implemented an identity graph\\
\textbullet{}  Managed a 28 node, 42+ TB Cassandra cluster in AWS for customer-facing dashboard\\
\textbullet{}  Admin of Pinot Startree cluster and ETL serving frontend dashboards\\
\textbullet{}  Served as an admin and architect for Snowﬂake, Sagemaker/EMR, Databricks

Cost Savings

\textbullet{}  Led upstream and downstream optimizations to reduce infrastructure costs, including application,

storage, governance, and business process workﬂow optimizations. Includes multiple \$500k+ eﬀorts.

\textbullet{}  Served as a key contributor in quarterly spend and revenue planning

\textbullet{}  Tracked and forecasted cloud costs across AWS and GCP organizations and supplementary services\\
\textbullet{} 

Implemented automated metrics to expose cost-to-revenue ratios across product lines and platforms

Observability

\textbullet{}  ETL and data quality and eﬃciency monitoring for peta-byte scale ingest and egress workﬂows\\
\textbullet{}  Developed data science centric job monitoring and analytics platform solutions\\
\textbullet{}  Conducted streaming checkpoint and lag analysis for real-time and batch process signaling

Streaming/ELT

\textbullet{}  Modular Spark Structured Streaming framework ingesting approximately 250 billion records per day

across various teams and products

\textbullet{}  Modular Flink streaming application to Delta Lake, processing 9 GB/s and 200 billion records daily\\
\textbullet{}  Adtech audience products with Databricks, AWS, Snowﬂake and GDPR/CCPA data compliance\\
\textbullet{}  Spark in Snowﬂake, Databricks, and AWS for critical ﬁnancial data and external data products\\
\textbullet{}  Serverless event-based ingest monitoring and auditing system for disparate data sets and workﬂows\\
\textbullet{}  Migration and greenﬁeld data processing applications with k8s, wired for auto-scaling in EKS\\
\textbullet{}  Kafka Connect ingestion from bare metal, geo-dispersed servers to S3

Infrastructure

\textbullet{}  Architect of AWS zero-trust multi-tenant organization and structure for Data Platform\\
\textbullet{}  Developed Kubernetes cluster with applications and pipelines for big data use cases\\
\textbullet{}  Created and managed on prem and cloud servers, applications, and databases with infra-as-code

TECHNICAL SKILLS

Frameworks

\textbullet{}  AI Agentic, MCP, Spark, Spark Structured Streaming, Flink, Lambda/Serverless, Glue, Kubernetes, Kafka

Connect, Event-driven, APIG/ALB, REST, FastAPI, ORM, OPA, Jinja2, Structured and Unstructured data

Databases/Storage

\textbullet{}  Vector DB’s, Databricks, GCS, Snowﬂake, EMR, Aerospike, Cassandra/ScyllaDB, Pinot/Startree, MySQL,

Postgres, DynamoDB, RDS, Redis, Hadoop, MapR, Hive, Looker, Hue, Zeppelin, EBS, on-premise Linux

Languages

\textbullet{}  Python, Go, Bash, Java, Scala, Rust

Infrastructure

\textbullet{}  Docker, AWS Networking (VPC, IG, TGW, R53, ALB, etc.), EKS/Kubernetes, Glue Data Catalog, EC2,

Airﬂow, Kafka, Kinesis, SNS, SQS, EventBridge, DataDog, Graphite/Grafana, VictorOps, Jenkins, GoCD,

Vagrant, VirtualDock, Terraform, Terramate, Ansible, Helm, Cloud Formation

AI/LLM

\textbullet{}  Harness Engineering, Claude, Cursor, Codex, LoRA tuning, LangFlow, LangGraph, RAG analysis,

Lookalike Modeling, Traﬃc Shaping, Agentic workﬂows, Ollama, LangChain, PyTorch, TensorFlow

Creighton University | B.S. in Business Intelligence Analysis

EDUCATION \& CERTIFICATES

AWS Solutions Architect - Professional Level

Databricks Lakehouse Architecture

HOBBIES

AI, Classic Car Restoration, Welding, Wine-making, Snowboarding, Outdoors, Piano, Electronics, Exercise
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