Sriram Rao

Software Engineer

Software engineer specializing in large-scale data management systems. Proven track record developing efficient, scalable backend solutions and collaborating to drive innovation. Expertise in distributed workflow orchestration, query processing, and ML-assisted automation, paired with strengths in cross-functional communication, teaching, and research partnerships to deliver complex systems that land with users.

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Selected Projects

Rush

Lightweight, extensible workflow manager in Python with JSON-based job definitions. Built for rapid prototyping of batch pipelines and internal tools.

GenIE

PostgreSQL plugin for implicit invocation of external data generators via UDFs. Lets queries call tools seamlessly as if they were native functions.

www.sriramrao.com

Personal site built with Svelte and TypeScript. Designed for minimalism, speed, and full control over layout, animations, and content.

Diary Card (Read why I built this)

An iOS app to log my daily mood measures, tailor-made to my specific use cases, behaviour and preferences.

Code/Job Assistant

CLI tooling that rewrites resumes, cover letters, and LinkedIn copy using LLM prompts tuned to each job post. Faster than waiting for recruiters— read how I vibe-coded it.

Work Experience

Graduate Researcher University of California, Irvine

Latency-aware data management and distributed systems research

Sep 2020 to Sep 2024

Designed a PostgreSQL plugin that balances latency and cost for ML forecast workloads by scheduling compute across live and predictive queries.
Developed a framework to invoke environmental simulators (e.g., HYSPLIT) implicitly during analysis so domain scientists could run models inline.
Collaborated with civil engineers, chemists, and physicists to build backend systems for IoT networks monitoring prescribed fires.
Authored a lightweight DAG workflow runner in Python to orchestrate research pipelines (open-sourced as sriram-rao/rush).

Software Engineer - PhD Intern Dremio

Lakehouse query performance through progressive planning

Jun 2022 to Sep 2022

Software Engineer Microsoft

Data platform. Large-scale data-intensive systems

Jun 2016 to Sep 2020

Owned Bing Ads experimentation framework processing billions of ad-serving requests daily to compute metrics for trigger-string experiments in under 20 minutes.
Rebuilt an ETL workflow manager that coordinated 100+ pipelines; cut deployment time from an hour to under five seconds.
Led a Spark Streaming POC that delivered A/B experiment results 3x faster than the previous batch system.
Refactored an Azure-hosted API cache layer with aspect-oriented patterns, eliminating repetitive configuration code.
Reviewed 40+ designs and 100+ code changes to keep data platform services reliable at scale.

Intern Microsoft

Kusto, MongoDB, column-store: performance analysis

May 2015 to Jun 2016

Intern Bilent Services

Web dev: AngularJS API, parallax scroll UI

May 2014 to Jul 2014

Academia

Teaching Assistant University of California, Irvine

Instruction for large-scale data management and programming courses

Sep 2020 to Dec 2024

Skills

Core Languages PythonC#JavaC++CSwiftRubyLispPrologSQL

Databases Big DataSQLNoSQLMongoDBRedisOLAPOLTPPostgreSQLColumn storesIcebergInfluxDBTrino

Compute Platforms SparkTrinoAthenaClickhouseETLQuery EnginesCalciteSpark SQLApache CalciteDistributed DAGsProgressive Results

Backend .NETSpringFlaskSvelteKitCachingRESTMicroservicesArchitectureDistributed SystemsRailsAOP

UI/UX HTMLCSSJavaScriptTypeScriptSvelteSwiftUITailwindCSSdaisyUIGrafana

Automation & Infrastructure BashPowershellLuaDockerAzureAWSCI/CDCustom IaCML-assisted Tooling

Data Science NumPyPandasMatplotlibSciPyScikit-LearnGeoPandasShapelyStatsmodelsXGBoost