Ben Creech - Resume

Benjamin P. Creech

Jersey City, NJ | ben@bpcreech.com | https://bpcreech.com | linkedin.com/in/bpcreech

SOFTWARE ENGINEERING TECHNICAL LEADER

Accomplished software engineering tech lead and manager with a track record in overseeing both technological and managerial growth within dynamic teams. Successfully built and ran several multi-level organizations of 15+ developers each, at Bloomberg, Google, and Via Transportation Inc. Extensive background spans SaaS micromobility backend development, online payments, financial portfolio analysis, real-time HPC SONAR simulation, flight simulation, SSO integration, and workstation fleet management. Demonstrated ability to drive team success in diverse technical domains, ensuring optimal performance and alignment with organizational goals. Open to work in the NYC area or remotely.

AREAS OF EXPERTISE

TECHNICAL SKILLS

Programming and Markup Languages: Python | C/C++ | Java | Go | TypeScript | JavaScript | sh | Fortran | Ada | Perl | XML | XSD | XSLT | HTML.

PROFESSIONAL EXPERIENCE

Via Transportation, Inc, New York, NY 04/2024 – Present

Director, Rider Account NY

The Rider Account organization owns the backend systems for logins, comms, eligibility status, payments, and history for millions of users of hundreds of Via transit services worldwide. The New York contingent complements the Tel Aviv site, with co-ownership of a broad set of components.

Built this team from zero, starting from no engineers working on the core Via product in the entire US region.
Created and drove the multi-year roadmap for re-engineering rider payments logic, with incremental deliverables aligned with business goals and partner needs. This involved, e.g., seamlessly pivoting the core payment method data model from unary to N-ary, converting a one-shot pricing system to a continuous process, implementing multi-tenancy through Stripe Connect, and transforming an overly complex on-session payment system for Apple and Google Pay to off-session.

Oversaw, designed, and in many cases personally implemented and launched diverse projects—from capping rides in a paratransit service (an 8-team project), to integrating automated subscription management with a partner’s bespoke API, to urgently reimplementing a ride reporting system used by a large multi-tenant partner. These projects were critical to retaining tens of millions in revenue from these customers.
Pushed paydown of the hefty tech debt accrued by this 12-year-old startup, including starting up an internal site for modern coding best practice and code review standards, successfully advocating for company setup of anomaly detection in Sentry, creating and executing on an integration test modernization plan, and writing and deploying several linter tools geared to a 500k LOC legacy Python codebase. This strategy enabled continued feature development while ramping up area stability for the company IPO in late 2025.
Acted as primary technical editor for the public Via engineering blog.

Google LLC, New York, NY 10/2018 – 04/2024

Senior Software Engineering Manager (TL/M, L7), Cloud Ecosystem

The Corp Eng Cloud Ecosystem team addresses the cross-cutting concerns of several thousand Google-internal developers as they develop for Google Cloud Platform (GCP).

Directed the seamless containerization of critical workloads and enhanced software supply chain integrity. Drove the modernization of a GCP Serverless-based low-code application platform, leading strategic initiatives for adoption of serverless, Kubernetes, and cloud-based ML in Corporate Engineering and partner orgs.

Built a 1-site 4-engineer team into a 5-site 18-person team, fostering collaboration and efficiency, resulting in 10 promos and one IC-to-manager conversion.
Built a next-gen containerized serverless solution for >1k internal applications, saving hundreds of millions in total rewrite costs across the company. Core components of this work were later externalized in the GCP Serverless product suite.
Modernized and expanded a low-code application platform. Java + Angular Dart on GCP Serverless, using Google Cloud SQL, Datastore (NoSQL), etc. This platform serves a fleet of ~80 internal apps (example apps: cashflow risk tracking saving >$50 MM annually, invoice dedupe saving >$20 MM annually, PCB design management, …).
Led buildout and launch of an intent-driven infrastructure-as-code platform for internal use of GCP Serverless at Google.
Orchestrated a strategic reorganization, consolidating my 15-person Developer Infra/Cloud org into Corp Eng Cloud Applications and Runtimes, streamlining mission and competency alignment.
Wrote and lead writing of Java, Python, Go, Dart, and TypeScript, using industry-leading best practices for hermetic testing and coverage (Junit, Mockito, Selenium WebDriver, etc)
Developed impactful vision, roadmaps, OKRs, and KPIs, contributing to organizational clarity and goal attainment.
Established strong relationships (partnerships, shared OKRs, working groups) with global GCP teams, internal customer teams, security and privacy engineering, and SRE, enhancing cross-functional collaboration.
Led the organization's inclusion working group and facilitated a DEI book club, promoting a diverse and inclusive workplace culture.

Bloomberg LP, New York, NY 12/2010 – 9/2018

Engineering Team Lead, Portfolio Analytics, 4/2014 – 9/2018

The Bloomberg Portfolio Analytics group provided historical and real-time performance, attribution, characteristics, and risk analysis of user portfolios, funds, and indices. The integration team focused on building and connecting a microservice-based backend system composed of services mostly written in C++, Python, and Java, running on Linux, Windows, AIX, and Solaris.

Led the innovation and development of customer-centric custom calculation expressions within the portfolio analysis system, fostering adaptability and usability. Spearheaded the management of a diverse software engineering team, driving the adoption of Agile Scrum and Kanban processes, and successfully resolving performance and interpersonal challenges.

Developed, integrated, and launched two user-extensible calculation systems (text + graphical), enhancing the analytical capabilities of the portfolio analysis system.
Managed a team of up to 20 software engineers, providing guidance and coaching to leads of 2 sub-teams while fostering a collaborative environment with cross-functional teams.
Successfully integrated the engineering team with (finance) product, QA, sales, and support, ensuring a streamlined workflow.
Implemented new SDLC processes and tools around Github Enterprise and dpkg, enhancing efficiency in response to rapid departmental growth.
Led 24/7 production operations supporting our platform including observability, instrumentation, and operational intelligence (via e.g., Splunk), hardware planning, live performance tuning, and postmortem root cause analysis
Scaled the PORT product 3 orders of magnitude, to handle on-the-fly fixed income and derivative analysis, for >30k DAU each running >1yr time horizon analysis on >10k instruments.

Senior Software Engineer, Portfolio Analytics, 12/2010 – 4/2014

This was an individual contributor role which grew into the above leadership role.

Developed and integrated financial software calculation libraries into a service-oriented architecture primarily using C++ and Python on Linux.
Led the creation of the core calculation infrastructure for Bloomberg’s PORT function (a merger of Bloomberg’s Portfolio Attribution and Slice-and-Dice backends).
Supported and grew this infrastructure up through ~10k DAU.

Solomon Page, New York, NY 10/2010 – 12/2010

Senior Software Engineer Contractor

Portfolio Analytics

Worked for Solomon Page as a right-to-hire contractor, in Bloomberg’s Portfolio Analytics group. The contract ended when Bloomberg extended an offer to work in-house.

Developed ETL systems in Python for on-boarding third-party fixed income indices into Bloomberg for use in Bloomberg’s portfolio analysis system.

Science Applications International Corporation, Bethesda, MD 12/2006 – 10/2010

Simulation Software Engineer, Acoustic and Marine Systems Operation, System Engineering Products Division

Worked for SAIC (now Leidos) as a contractor supporting the US Naval Surface Warfare Center, Carderock Division (NSWC-CD).

Developed, improved, and validated an element-level real-time acoustic simulator/stimulator on TOP500 computer clusters. This software component was used in training systems (surface and submarine, shore-side and at-sea), predictive simulations, and developmental testing of new SONAR systems.
Designed and implemented new components and algorithms, re-engineered legacy software, and wrote validation tools including a real-time network-connected Python-based DSP GUI using numpy, matplotlib, and pygtk. This primarily involved C++ and Python on a very large IP-backplane computer cluster. Various open-source tools were employed, e.g. Linux, LAM (MPI), STL, Boost, GCC, SciPy, SQLAlchemy, and PostgreSQL.

ADDITIONAL RELEVANT EXPERIENCE

Science Applications International Corporation, Lexington Park, MD

Simulation Software Engineer, Simulation and Research Services Division, Reconnaissance and Surveillance Operation

Worked for the SAIC in Lexington Park, MD, supporting the US Naval Air Warfare Center Aircraft Division (NAWCAD).

Worked with aerospace engineering SMEs to modernize and improve fidelity of the MH-60R/S, AH-1W, and UAV physics models.
Integrated an F/A-18 simulator for the JPALS program.
Co-authored the Unified Command System (UCS) Computer Based Trainer, a low-cost trainer for the Army National Guard’s mobile all-purpose communications system.

North Carolina State University, Raleigh, NC

Systems Programmer

Worked for the College of Engineering computing branch, Information Technology and Engineering Computer Services (ITECS).

Wrote a Windows front-end for the MIT Kerberos libraries and Andrews File System (AFS), used on all campus Windows computers and many home PCs, to provide secure authentication and authorization to campus file system resources.
Created a self-deploying Microsoft Active Directory desktop platform for the College of Engineering staff.

EDUCATION

Master of Science (M.S.) in Computer Engineering

North Carolina State University

GPA 3.778

Bachelor of Science (B.S.) in Computer Engineering

North Carolina State University

GPA 3.864, Summa Cum Laude

Machine Learning by Stanford University & DeepLearning.AI on Coursera. Certificate, January 2024