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AI Late-Arriving Data Reconciliation Engineer

Grayson Martins

Full-time · Job · Denver

About the role

We built a data pipeline platform that moves billions of events into Snowflake for logistics and retail customers. Orchestration, schema checks and lineage are already in place and working. What still hurts is late data: events that arrive hours or days after their window closed, quietly breaking aggregates and model features. Customers notice when a dashboard number changes overnight. Your job is to fix that class of problem. You'll build detection for late arrivals, smarter backfill logic, and a scoring model that predicts which sources are likely to send late data so pipelines can wait or reprocess intelligently.

Responsibilities

  • Detect late-arriving records and measure their impact on downstream tables
  • Build targeted backfill jobs in Airflow that reprocess only affected partitions
  • Train a simple model that predicts lateness per source and time window
  • Partner with customer success to explain changes when historical numbers move

Requirements

  • Solid experience with Airflow or a comparable orchestrator
  • Strong SQL and comfort with Snowflake
  • Understanding of event-time versus processing-time semantics
  • Some exposure to streaming systems such as Kafka

Benefits

  • Remote within US time zones
  • Equity package
  • Health, dental and vision coverage
  • Annual home office stipend

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Categories

MLOps & AI Infrastructure data science & analytics

Skills

python airflow sql snowflake etl

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$80k – $100k / year

AI Expertise

MLOps & AI Infrastructure data science & analytics

Skills

python airflow sql snowflake etl kafka

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