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Aaru

AI-driven multi-agent forecasting platform

Data Engineer - Infrastructure

Data EngineeringConfirmed live in the last 24 hours
Full-timeNew York, NY, USA

About the Job

Requirements

  • Have at least 3 years of experience in data integration, data engineering, ETL/ELT, or a similar role involving large-scale datasets.
  • Have hands-on experience working with messy, high-volume data exceeding 100 TB and building systems that remain reliable at scale.
  • Be highly fluent in SQL and Python, and be comfortable with modern data infrastructure such as Snowflake, BigQuery, Databricks, or similar tools.
  • Exercise sound judgment around data quality and identify inconsistencies, edge cases, and integration risks.

Responsibilities

  • Build and maintain scalable pipelines to ingest, clean, and integrate large multimodal datasets.
  • Own data ingestion across APIs, flat files, cloud storage, and data warehouses.
  • Design workflows for linkage, entity resolution, deduplication, and schema harmonization across imperfect or incongruent datasets.
  • Work with engineering, research, and deployment teams to make integrated data usable for simulation ingestion.
  • Establish and monitor data quality checks, validation logic, and documentation across datasets and pipelines.
  • Help evaluate new data sources and determine how they can be joined with existing data assets.

Desired Qualifications

  • Have experience with alternative data, such as transaction data, clickstream, or geospatial data, from a hedge fund or data marketplace perspective.
  • Have experience building matching or entity-resolution systems across fragmented or noisy identifiers.
  • Have familiarity with privacy, compliance, and data licensing considerations when working with sensitive or third-party data.
  • Have worked closely with researcher or product teams to turn raw data from disjoint sources into an accessible structured database.
  • Have a background in statistics and familiarity with sampling biases, bot detection, imputation, and standard data quality metrics.

About the Company

Aaru

AI-driven multi-agent forecasting platform

Aaru uses multi-agent simulations to forecast outcomes in political polling, business strategy, and global issue modeling. It builds virtual models of real-world actors, runs scalable cloud simulations, and uses machine learning to turn results into actionable forecasts. It differentiates itself by applying multi-agent forecasting to deliver more scenario testing at a lower cost than traditional polling, serving major policy groups and Fortune 500 companies. Its goal is to expand beyond elections to tackle a broader set of societal and business challenges with AI-driven analytics for decision-making.

Company size
51-200
Company stage
Series A
Total funding
$50M
Headquarters
New York City, New York
Founded
2024

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