Amay Dave

As a data engineer, I am driven by an insatiable curiosity and determination to master complex challenges, constantly seeking innovative solutions. My ambition fuels a creative approach to problem-solving, where I strive to build and optimize data systems with an eye towards ideal, impactful results.

Experience

A

Data Engineer (Software Engineer)

AMDOCS · Jun 2025 – Present

Not yet confirmed

• Built end-to-end ETL/ELT pipelines using Kafka (real-time ingestion), Spark (processing), and Snowflake (data warehousing), unifying vendor data across enterprise domains and processing 1M+ vendor records.
• Designed the data layer and data model for a Third-Party Risk Management AI agent - standardizing vendor contract/breach histories into a fanout-free, similarity-mapped view (SQL + Python), cutting manual risk-review effort ~25%.
• Used Docker to containerize backend microservices into lightweight, portable images - ensuring consistent environments across dev/test/prod; deployed and orchestrated them on AKS with Helm, and built CI/CD pipelines with GitHub Actions for secure, enterprise-grade scalability.
• Configured Entra ID (MSAL) and JWT validation, and supported RESTful API integrations, strengthening access control and data-protection compliance.
• Built Grafana dashboards monitoring pipeline health and data quality (ingestion lag, job failures, volume anomalies), enabling proactive issue detection before compliance impact.

Software Developer

Amdocs · Aug 2023 – Present

Not yet confirmed

A

Data Engineer (Software Developer)

AMDOCS · Aug 2023 – Jun 2025

Not yet confirmed

• Developed an internal LLM-powered chatbot enabling natural-language queries over vendor and compliance data for business users.
• Designed automated reporting workflows and data pipeline architecture across multiple source tables, cutting manual reporting effort ~30%.
• Implemented automated data quality checks (row-count reconciliation, accuracy audits) across the migration pipeline to catch discrepancies early and ensure reliable Teradata-to-Snowflake data movement.
• Streamlined reporting, reducing turnaround time ~40% and improving data accessibility for business and compliance teams.