Anmol Suri

Senior Software Engineer

Bengaluru, Karnataka, India4 yrs 8 mos experience

AI ML PractitionerAI Enabled

Key Highlights

Designed AI-powered test coverage analysis pipeline.
Implemented GDPR-compliant regional S3 storage.
Developed robust ELT solutions for large-scale data systems.

Stackforce AI infers this person is a Backend-focused Software Engineer with expertise in SaaS data systems and cloud-native solutions.

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Skills

Core Skills

Artificial Intelligence (ai)Large Language Models (llm)JavaObject-oriented Languages

Other Skills

RegexMySQLGitHubAWSAzureGitUnit TestingComputer ScienceObject-oriented Programming (OOP)AlgorithmsData StructuresSQLHTMLGoogle Cloud Platform (GCP)Amazon Web Services (AWS)

About

Backend-focused Software Engineer with 5+ years of experience building and scaling distributed data systems and cloud-native ETL pipelines. Specialized in Java-based data connectors, handling large-scale structured and semi-structured data ingestion with a focus on performance, scalability, and reliability. Experienced in optimizing data pipelines and architecting efficient ingestion frameworks. Proficient in leveraging AI tools such as Claude Code, Copilot, and ChatGPT Codex to build automation systems and improve engineering productivity.

Experience

4 yrs 8 mos

Total Experience

4 yrs 8 mos

Average Tenure

4 yrs 8 mos

Current Experience

Fivetran

3 roles

Senior Software Engineer

Promoted

Mar 2025 – Present · 1 yr 2 mos

Designed and built an AI-powered test coverage analysis pipeline that identified 70% missing E2E test coverage across 400+ API connectors, by orchestrating a 5-stage Claude LLM pipeline that extracts feature combinations from connector DSL definitions, performs semantic matching against existing test suites, and generates prioritized gap reports directly shaping the team's quarterly test backfill roadmap.
Designed and implemented Multi table merge mode feature for system exported files to map data into separate tables into single schema based on the regex file pattern and folder path provided by the User. (ARR from connections with > 1 table grew by 4.2x month-over-month for S3, SFTP, Azure Blob, Google drive, GCS)

Artificial Intelligence (AI)Large Language Models (LLM)

Software engineer II

Mar 2023 – Feb 2025 · 1 yr 11 mos

Implemented regional S3 bucket storage for an email connector (POC and implementation), ensuring full compliance with GDPR regulations
Enabled range-specific Excel files reading for Connectors like Google Drive and Box.
Built Apache Iceberg: Connector that reads files from Iceberg file formats in AWS S3.
Implemented XML file reading in packed and unpacked modes using a valid XSD after a successful POC.
Developed Merge Mode for file-based connectors, enabling data sync from multiple files to a single table in the data warehouse.
Technologies used: Java, Bazel, MySQL, GitHub, IntelliJ, AWS, Azure, CloudBeaver, New Relic, OOPS, Concurrency, Snowflake, Databricks, Buildkite, PostgressOL.

Object-oriented LanguagesJavaMySQLGitHubAWSAzure

Software Engineer

Aug 2021 – Mar 2023 · 1 yr 7 mos

Part of the Research & Development team.
Worked on the connector side in the ELT Data Pipeline to design and develop robust solutions to meet client requirements for functionality, scalability and performance of the File connectors like S3,SFTP,GCS etc.
Add support for Magic/merge mode to sync data from cloud file connectors using Box, Sharepoint, Dropbox connector.
Also Worked on performance Benchmarking project to analyze the syncing speed of Extract,process and load in File Connectors.
Worked on a POC to add XML file support using a valid XSD.
Tools & technology: Java, Git, Height, Figma, Azure, AWS, IntelliJ Data Structures and Algorithm, OOPS

JavaGitAWSAzure