Engineering an institutional investment platform at scale

The work

Pension funds, endowments, foundations, and family offices need to understand investments spread across public and private markets. Portfolio analytics brings performance, risk, exposure, and liquidity information together so investment teams can assess complex portfolios and explain them to stakeholders. The platform I worked on served institutional asset owners operating at substantial financial scale.

I was one of the senior database engineers responsible for the production data environment and database development behind that platform. I worked with application developers, analytics engineers, infrastructure specialists, and client services on problems that crossed team boundaries. My responsibility was to connect what users experienced with the application requests, calculations, and database behavior producing it.

In one performance initiative, a calculation-intensive investment reporting process took approximately two hours to complete. I investigated the SQL execution and optimized the reporting implementation, reducing runtime to under three minutes. That gave users a much shorter wait for financial analysis and provided a concrete measure of the value of the database work.

Across separate application-performance initiatives, I worked with developers on repeated database calls, dashboard initialization, expensive calculations, and workload distribution. The engineering involved execution plans, Query Store, indexing, set-based processing, partitioning, and columnstore structures. It required understanding when to improve the SQL and when to change the way the application asked the database to work.

My broader platform responsibilities included an Azure-to-Google-Cloud modernization spanning Windows, Linux, and SQL Server versions in a multiterabyte environment. As part of the engineering team, I contributed database performance, compatibility, high-availability, and operational-readiness work. Workload replay, load testing, and telemetry helped evaluate configuration choices and identify regressions before production changes.

I also took ownership of improvements to database access governance: replacing accumulated individual grants with defined access groups, management approval for privileged access, operating documentation, and evidence for audit review. I supported source-controlled database releases and production change review, where a schema or index change had to be considered in the context of a running financial application.

Recovery was another part of that responsibility. When financial records were deleted while production continued processing, I used a separate restored database to support targeted recovery and coordinated validation of the recovered information and its dependent calculations. The recovery approach preserved the distinction between repairing affected records and rolling back the whole production system.