Senior Data Engineer, Data Engineering

Plaid

Confirmed live 2 days ago High trust

Quick summary

Work type
On-site
Location
San Francisco, CASeattle, WA
Salary
$190,800–$238,800 / yr
Posted
7 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $173k
This role $215k
$120k most similar roles pay here $251k

This role pays more than 82% of similar roles. Most pay $140,000–$206,041 — the shaded band above. At the midpoint, this role pays about $215k versus about $173k for comparable roles.

Based on 240 similar postings.

Employer

About Plaid

Plaid is a financial technology company that builds a data network powering digital finance applications, enabling consumers to securely connect their financial accounts to apps and services. Industry: Financial Technology & Data Infrastructure

Plaid currently has 35 open roles on FindRole.

Listed pay typically runs $190,800–$262,800 across 35 roles with salary data.

Most-posted roles

View all roles at Plaid

At a glance

TL;DR · Senior Data Engineer, Data Engineering

Senior Data Engineer - Data Engineering joins a team dedicated to scaling data systems while maintaining high standards for accuracy and completeness. In this role, you will build and manage core SQL and Python data pipelines that power the company's data lake and warehouse. You will be responsible for designing golden datasets, ensuring data quality and performance, and creating well-documented infrastructure with defined SLAs. The work involves solving complex pipeline issues at scale, evolving analytics schemas from unstructured data, and managing low-level data infrastructure. You will utilize a technical stack including DBT, Airflow, Redshift, Atlan, Retool, Spark, Kafka, Snowflake, and Databricks. This position focuses on the core problem of providing reliable, high-quality datasets to internal teams across engineering, product, and business units to enable faster, data-driven decision making for financial services.

What does a Data Engineer earn in California?

Median $199800 from 35 postings across 19 companies.

See salary data

What you'll do

  • Own core SQL and Python data pipelines that power the company's data lake and warehouse.
  • Design and maintain high-quality datasets with defined uptime, performance, and usage standards.
  • Build and manage batch and real-time data pipelines using tools like Spark and Kafka.
  • Develop analytics schemas from unstructured data to support internal reporting and business intelligence.
  • Lead large-scale data engineering projects that require cross-functional collaboration across the organization.
  • Manage and improve low-level data infrastructure to ensure system reliability and scalability.
  • Create proof-of-concepts for new technologies to balance technical advancement with user adoption.
  • Advocate for industry best practices and tools to improve data strategy and integrity.

What we're looking for

  • You must have 4+ years of dedicated data engineering experience solving complex pipeline issues at scale.
  • You must have experience building data models and pipelines on large datasets ranging from 500TB to petabytes.
  • You must be proficient in SQL and Python for building data pipelines.
  • You must have experience with modern SQL orchestration tools such as DBT, Mode, and Airflow.
  • You must have experience working with performant warehouses and data lakes like Redshift, Snowflake, or Databricks.
  • You must have experience building and maintaining batch and real-time pipelines using technologies like Spark and Kafka.
  • You must be able to design analytics schemas on top of unstructured data.
  • You must demonstrate the ability to collaborate with cross-functional stakeholders to balance infrastructure and business needs.

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