Saquib B.

About Saquib B.

I build data pipelines, automate workflows, and use AI to make data teams move faster.At SimpleTire (now Dealer Tire), I automated ingestion workflows that saved my team 16+ hours/week, built ELT pipelines that uncovered $1.6M in inventory discrepancies, and designed dashboards tracking $2.4M in variances for supply chain planning. I also built an LLM-powered agentic workflow that ran cross-entity SQL analyses and generated structured reports for Finance and Supply Chain stakeholders, cutting hours of manual reporting.Now I\'m building data anonymization pipelines at RBC Tech and leading a data engineering team at Saayam for All, a nonprofit where I design multi-source aggregation pipelines on AWS, architect synthetic test datasets across 35+ tables, and set up CI/CD for automated deployments.CS and Math from Drexel. I sit at the intersection of data engineering, analytics, and AI, and I\'m most excited about using agents and LLMs to automate the tedious parts of the data lifecycle so people can focus on decisions, not data prep.Tools: Python, SQL, Snowflake, AWS (Lambda, S3, EventBridge), Sigma, LLM/agent integrations.Open to Data Engineering, Data Science, and Analytics roles where I can build systems that actually move the needle.

Experience

1. Data Engineer Team Lead

   Saayam For All

   Dec 2025 — Present · US

   Saayam for All is an open-source nonprofit platform that connects people in need with volunteer organizations.• Design and deploy multi-source data aggregation pipelines on AWS Lambda that query PostgreSQL, invoke a GenAI microservice for AI-ranked results, and filter an IRS nonprofit dataset from S3, merging all three into a unified, deduplicated API response with source tagging and graceful degradation.• Build EventBridge-scheduled Lambda pipelines that aggregate platform KPIs from Aurora/Postgres and persist daily JSON snapshots to S3, decoupling the frontend from direct database access.• Architect and generate synthetic test datasets spanning 35+ tables with enforced referential integrity, internal consistency, and realistic distributions, enabling teams to build and test pipelines end-to-end before production data is available.• Coordinate frontend integration, working with the web app team to replace static mock data with real-time context-aware organization suggestions, implement cold start loading states, and build error fallbacks.• Lead a 10+ person data engineering team with ~97% contributor churn, restructure the repo for modularity, establish CI/CD via GitHub Actions for automated Lambda deployments, and author onboarding docs that reduce ramp-up from days to hours.• Drive cross-functional alignment across Data, GenAI, and Frontend teams, defining API contracts, response schemas, and integration patterns across three independent repositories.• Document the end-to-end data flow architecture from source tables through Lambda processing to S3 delivery and frontend consumption, creating system diagrams and data dictionaries as the single source of truth.

Education

• Drexel University

  Bachelor of Science - BS, Computer Science

• Drexel University

  Bachelor of Arts, Mathematics