Senior Data Infrastructure Engineer — Scale Data Pipelines

Plaid

United States

On-site

USD 150,000 - 210,000

Full time

14 days+

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Job summary

Plaid is building the data infrastructure that powers billions of financial decisions. We scale data pipelines, ensure data freshness, and provide a robust platform for analysts and engineers to derive insights. You will own critical backend data systems and help drive scalable, reliable data solutions across Plaid.

The team emphasizes mentorship, collaboration, and delivering high‑impact data infrastructure at scale, with opportunities to work across multiple product lines and geographies.

Qualifications

  • 6+ years of software engineering experience.
  • Extensive hands‑on software experience in Data Infrastructure or Platform domains.
  • Strong cross‑functional collaboration, communication, and project management skills.

Responsibilities

  • Contribute towards the long‑term technical roadmap for data‑driven and machine learning iteration at Plaid.
  • Lead key data infrastructure projects such as improving ML development paths, offline streaming for data freshness, ETL pipeline infrastructure, and data warehouse/lakehouse evolution.
  • Work with stakeholders across teams to define technical roadmaps for backend systems and abstractions across Plaid.
  • Debugging, troubleshooting, and reducing operational burden for the Data Platform.
  • Grow the team via mentorship and leadership, review technical documents and code changes.

Skills

6+ years software engineering
Data infrastructure experience
Cross-functional collaboration

Tools

Databricks
Airflow
AWS EMR
Python

Job description

Plaid is building the data infrastructure that powers billions of financial decisions. We scale data pipelines, ensure data freshness, and provide a robust platform for analysts and engineers to derive insights. You will own critical backend data systems and help drive scalable, reliable data solutions across Plaid.

The team emphasizes mentorship, collaboration, and delivering high‑impact data infrastructure at scale, with opportunities to work across multiple product lines and geographies.

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