Soundarya Mattikatti

Orchestrated and automated robust cloud-native data pipelines using AWS Lambda and S3, significantly streamlining data flows for investment analytics and minimizing manual intervention within an investment banking environment.

Developed custom Python and SQL-driven pipeline routing solutions and data transformation workflows, successfully integrating diverse financial data sources and enhancing data accuracy and consistency across internal datasets.

Collaborated with investment analysts to translate complex financial datasets into actionable reports and dashboards, improving data transparency and substantially reducing manual data reconciliation efforts.

Architected and maintained production pipelines in Azure Data Factory for daily finance datasets, improving efficiency by approximately 20% through pipeline refactoring and optimized scheduling.

Orchestrated high-volume ETL (TB-scale/day) processes, reducing processing time from 8 hours to 2 hours using parallelization, incremental loading, and SQL performance tuning, enabling same-day reporting.

Led end-to-end migration of legacy finance systems to Azure, transferring 5+ years of historical data with zero data loss, implementing validation controls and reconciliation checks for a controlled cutover.

Built robust ETL workflows integrating multiple enterprise sources (including SAP ECC) using ADF, ADLS, and SQL Server stored procedures, delivering datasets/KPIs for Finance, Operations, and HR across three business units.

Improved query execution time by approximately 40% with advanced SQL tuning and indexing, supporting ten times growth in concurrent users.

Implemented CI/CD practices for data pipelines in Azure DevOps, standardizing deployments and reducing production issues.

Contributed to embedded systems development across 3+ product lines, participating in design and code reviews that identified and resolved 25+ performance bottlenecks, improving system efficiency by 15%.

Diagnosed and resolved 40+ complex product issues using systematic debugging, reducing critical system failures from 15% to 5% and enhancing overall product reliability.

Collaborated with hardware product teams to build data-gathering devices, achieving 99.2% data collection accuracy and supporting analytics for 10+ client deployments.

Participated in agile development cycles, contributing to 8+ sprint deliveries and maintaining a 95% on-time delivery rate for high-quality software solutions within strict project deadlines.

Authored technical documentation and user guides for 5+ product modules, improving knowledge transfer efficiency and reducing new team member onboarding time from 4 weeks to 2.5 weeks.