As a Senior Data Engineer, I supported the most important Company-level workstreams and was held accountable to deliver scalable and well-governed data solutions that could easily be used by Client Engineering and Ranking Engineering Teams across the Company.

In this role it is a given that every DE is expected to proactively identify and mitigate inefficient Spark jobs and data storage patterns. In addition to being held accountable to deliver warehouse efficiency, the core expectation for Senior DE's is to proactively identify new systems and technologies for the org to adopt, and then work with SWE, DS and PM partners to drive adoption towards measurable, impactful shared goals.

In this role I spearheaded a project in partnership with Ranking engineering to overhaul inefficient video ranking pipelines which yielded more than $800k in annual savings through compute (Query Optimization) and storage savings (Schemas and Data Footprint). My strategic efforts focused on onboarding our org to a new logging stack where I worked in Hack to add in new server logging, designed the downstream data schemas to translate the machine-friendly output into analytics-friendly tables, and laid out the roadmap for reconciling the new logging stack with the old in order to validate and build trust in the new infra.

In addition to this core Product work, I was also the Leader for our company-wide Dashboarding Excellence program. As leader of this program for Facebook App, I was responsible for working with Directors across Product and Engineering Orgs to roadmap and delegate new core dashboarding infrastructure and Features such as pageload metrics and tracking, automated dashboard linting functionality, and dashboard certification features. These features are now used by every dashboard consumer in the company, and allowed us to ensure VP and C-Level executives knew which dashboards were well-supported, their formatting was consistent, and they loaded fast.

I supported the core SWE, DS and PM Teams responsible for preventing data leakage of users via publicly available endpoints. I was responsible for building metrics and heuristics that relied on 2 trillion records of data per day. Our metrics and dashboards were used at VP-level to make decisions on infrastructure and SWE investments and roadmaps.

This role was a lot of fun as it involved close partnership and ideation with some of the best security engineers in the world. We resolved technical challenges such as how to represent the concept of ‘endpoint’ across any public-facing API / language that could exist at Meta, and then we needed to build out ETL pipelines and consolidated metrics, reporting and dashboards for each of those potential endpoints depending on the language and tech stack they used.

After building the Audience Network product and analytics team to maturity in London, our analytics team broadened our scope to include Facebook's only B2B product "Workplace". Alongside my daily responsibilities as a Data Scientist, I used Hack to build out new benchmarking and adoption reporting tools that allowed client teams to print out detailed customized reports without the need for DS support or manual data analysis.

I also had the privilege to support the growth of Analytics in the Workplace Product organization by building and mentoring a team of 6 new data scientists who in turn supported ~120+ global Customer Success Managers.

I spent 4 amazing years supporting Facebook's Audience Network. I leveraged my strong analytics capabilities and found myself as one of the core contributors to the design and implementation of our network-wide quality metrics and infrastructure. Our success in this area demonstrated to Meta Company-Level leadership that we could quantifiably drive incremental advertiser value by delivering Facebook ads outside of Facebook Owned and Operated surfaces. Our work drove the growth of Audience Network from a 5-figure business to a $3B+ annual revenue industry leader.

I was also proud to be invited to be a speaker at two of our annual Audience Network customer conferences held across China, Singapore, Hong Kong and Japan. In 2017 Meta offered me a contract to move to London to be part of the landing team to finally coalesce the Audience Network Product teams into a single global HQ.

As a TAM at LiveRail, I managed and enhanced API integrations and strategic partnership with LiveRail's largest customer (responsible for > 40% of LiveRail' revenue). I collaborated with both Internal and External Account Teams, Engineering and C-Level leadership to ensure growth targets, product strategies, and technical constraints were well-aligned.

LiveRail had a successful exit in Q4 2014 with a sale to Facebook (Meta).

I built and led a team of 3 Operations Analysts responsible for the maintenance, automation and reporting of ad revenue across 80+ websites. Reported directly to CTO where I was also responsible for designing and migrating to a new in-house ad serving platform.

I was a part of HSBC's 2-year Global Banking and Markets Analyst Rotational program. We focused primarily on Excel and VBA reporting and automation in support of the Credit and Rates Trading desks as well as Market Risk Management teams where we built consolidated daily risk exposure metrics which were reported to Financial Regulators.