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Peter Luro

Peter Luro
I build data systems for financial workflows — validation pipelines, ingestion frameworks, and trading infrastructure that operate reliably in production. Currently at Talcott Resolution, where my work feeds directly into hedging, reporting, and actuarial processes. My primary tools are Python and SQL. I focus on systems where data quality matters: catching schema drift before it reaches downstream consumers, designing for failure modes, and keeping pipelines maintainable as requirements evolve.

Open To

Market Data Engineer Senior SWE — Backend / Data Quantitative Engineer Trading Systems Engineer

Current Focus

  • Building Azure Container App services that give actuaries on-demand XLSX report generation without touching batch infrastructure
  • Configuring Autosys job scheduling for production workflows with structured error handling and dependency chains
  • Designing and implementing file loading strategies into a SQL Server data lake, handling complex source formats and schema variation at ingestion
  • Provisioning Azure resources and pipelines to support nightly hedging batch processes ensuring reliable, environment-aware execution across DEV/QA/PTE/PROD

Work Highlights

Full details on the Projects page.

Financial Data Validation Platform Python pipelines that detect schema drift, stale data, and identifier mismatches across Oracle and SQL Server before they reach downstream risk workflows.
Azure Ingestion Pipelines Containerized jobs with retry logic, structured logging, and environment-aware execution for processing large financial datasets at scale.
Trading Execution System Personal project: ingests intraday market data, evaluates EMA and breakout conditions, and submits orders through Alpaca's API with PDT compliance built in.

Approach

Systems I build are:

  • Predictable — fail loudly with clear signals, not silently
  • Honest — documented assumptions, explicit schemas, typed where it matters
  • Maintainable — readable by the next engineer without a walkthrough
  • Useful downstream — consumers shouldn't need to work around my output

Location

Open to opportunities in:

  • Boston
  • Florida
  • Utah
  • Texas
  • Remote