Aishwarya Sahai

Software Engineer

San Francisco, California, United States5 yrs 7 mos experience

Most Likely To Switch

Key Highlights

8+ years of experience in top tech companies.
Expert in building scalable data and cloud platforms.
Proven track record of optimizing complex engineering workflows.

Stackforce AI infers this person is a SaaS-focused Software Engineer with expertise in data engineering and cloud platforms.

Contact

025aish@gmail.com LinkedIn

Skills

Core Skills

Data EngineeringCloud PlatformsSoftware DevelopmentData ManagementDistributed Systems

Other Skills

AWS CloudFormationAmazon EC2Amazon ECSAmazon S3Amazon Web Services (AWS)AngularJSAnsibleApache IcebergApache KafkaApache PigApache SparkApache SupersetAzure Data FactoryAzure Data LakeAzure Databricks

About

I’m a Software Engineer with 8+ years of experience at Bloomberg, Apple, and Microsoft, building data and cloud platforms that scale. I love tackling complex engineering challenges, from designing distributed systems to optimizing pipelines that handle millions of queries and petabytes of data, all while keeping systems reliable and high-performing. Across my work, I focus on creating impact—whether it’s speeding up client onboarding, improving system resiliency, or enabling teams to make faster, smarter decisions. I thrive in fast-paced environments where I can drive cross-team initiatives and turn ambitious ideas into production-ready solutions. Core skills: Distributed Systems • Data Engineering • Cloud Platforms (AWS, Azure) • Apache Spark • Kafka • Kubernetes • Python • Scala • Java • C++ • Systems Design • Databases

Experience

5 yrs 7 mos

Total Experience

1 yr 2 mos

Average Tenure

2 yrs

Current Experience

Bloomberg

2 roles

Software Engineer

Promoted

Jun 2024 – Present · 2 yrs · Hybrid

Driving enterprise-scale data ingestion and data management workflows, enabling faster client onboarding, scalable query handling, and high system reliability with key contributions-
Built a modern data lakehouse with unified metadata and schema management, eliminating client-specific code and reducing client onboarding time from 3 months → under 1 week.
Architected and deployed a dedicated ingestion cluster for enterprise-scale data pipelines, achieving 99.99% uptime and reducing ingestion failures by 60%.
Scaled workflows to support 5M+ monthly queries and 4M+ ingestion requests, ensuring resilient and efficient ingestion operations.
Partnered with product and business stakeholders to align data onboarding workflows with enterprise reporting needs, enabling seamless, scalable client integrations.

Data EngineeringCloud PlatformsApache SparkKubernetes

Software Engineer

Jan 2023 – Jun 2024 · 1 yr 5 mos · Hybrid

Worked on the Portfolio Positions team, building scalable ingestion workflows and modernizing services for enterprise reporting.
Added features to core backend services for portfolio management, handling ~1M datapoints daily and ~500K outgoing queries, improving system throughput and reliability.
Reengineered a legacy C++ service into Python with enhanced observability and maintainability.
Aligned ingestion workflows with business reporting needs through collaboration with client-facing teams.
Mentored a summer intern, enabling them to deliver a production-grade feature.

PythonC++Software Development

Apple

Software Engineer Intern

May 2022 – Aug 2022 · 3 mos · Cupertino, California, United States

As part of Apple Cloud Services’ Trust & Safety team, I focused on observability and reliability at scale.
Designed and deployed a Message Loss Detection system across 50+ microservices, reducing detection time by 40%.
Instituted a distributed tracing and visualization framework with unified instrumentation, improving observability coverage by 70%.
Built a scalable foundation for future streaming workloads.

ObservabilityReliabilityCloud Platforms

University of massachusetts amherst

Graduate Teaching Assistant

Jan 2022 – Dec 2022 · 11 mos · Amherst, Massachusetts, United States

Served as a TA for the CS446 : Search Engines course, supporting students in information retrieval concepts and practical applications.
Mentored students on course topics and guided them through lab projects and assignments.
Led weekly lab sections to reinforce lecture material with hands-on learning.
Monitored and responded to student queries on Piazza, ensuring timely academic support for 60+ students.
Graded exams and assignments, maintaining fairness and consistency in evaluation.

Microsoft

Software Engineer 2

May 2019 – Aug 2021 · 2 yrs 3 mos

As part of Microsoft’s Cloud + AI org, I worked on enterprise-scale data management systems, focusing on trust, compliance, and efficiency.
Led the cross-team delivery of an audit module across 6 teams, improving user trust by 10% (89% → 99%).
Defined requirements with PMs and compliance stakeholders to meet enterprise and regulatory needs.
Optimized orchestration pipelines (processing 400+ datasets daily) with a 65% runtime reduction.
Mentored an intern to successfully deliver a production-grade feature.

Data ManagementCloud Platforms

Pegasystems

Cloud Development Engineer

Nov 2018 – Apr 2019 · 5 mos

As part of the Provisioning Engine Team, I worked on cloud-native deployments and platform scalability at enterprise scale.
Delivered new features on the Pega platform in AWS, enhancing scalability and supporting 100K+ daily client transactions.
Deployed and containerized Pega products using AWS, Docker, and Kubernetes, cutting deployment time by 50%.
Streamlined cloud adoption for 20+ enterprise applications, enabling faster client onboarding and feature delivery.

Cloud-native deploymentsPlatform scalabilityCloud Platforms

Unitedhealth group

Software Engineer

Jul 2016 – Oct 2018 · 2 yrs 3 mos

As a Software Engineer at UnitedHealth Group, I worked on distributed data systems powering provider directories and healthcare data pipelines at scale. Key achievements include:
Built a scalable open-source solution to match patients with the nearest healthcare providers, eliminating reliance on costly third-party software → $2.7M in annual licensing savings.
Engineered backend systems processing 10+ TB of healthcare data daily across 50M+ records, improving query performance by 35%.
Designed and optimized ETL pipelines and distributed data workflows (Hadoop, HBase, Pig, MapReduce, Elasticsearch) to support enterprise healthcare applications.
Delivered high-performance systems that powered provider directory accuracy and improved patient access to care.

Distributed SystemsETL