Responsibilities
- Understanding different aspects of the Plaid product and strategy to inform golden dataset choices, design and data usage principles.
- Have data quality and performance top of mind while designing datasetsLeading key data engineering projects that drive collaboration across the company.
- Advocating for adopting industry tools and practices at the right timeOwning core SQL and python data pipelines that power our data lake and data warehouse.
- Well-documented data with defined dataset quality, uptime, and usefulness.
Qualifications
- 4+ years of dedicated data engineering experience, solving complex data pipelines issues at scale.
- You’ve have experience building data models and data pipelines on top of large datasets (in the order of 500TB to petabytes)
- You value SQL as a flexible and extensible tool, and are comfortable with modern SQL data orchestration tools like DBT, Mode, and Airflow.
- You have experience working with different performant warehouses and data lakes; Redshift, Snowflake, Databricks.
- You have experience building and maintaining batch and realtime pipelines using technologies like Spark, Kafka.
- You appreciate the importance of schema design, and can evolve an analytics schema on top of unstructured data.
- You are excited to try out new technologies. You like to produce proof-of-concepts that balance technical advancement and user experience and adoption.
- You like to get deep in the weeds to manage, deploy, and improve low level data infrastructure.
- You are empathetic working with stakeholders. You listen to them, ask the right questions, and collaboratively come up with the best solutions for their needs while balancing infra and business needs.
- You are a champion for data privacy and integrity, and always act in the best interest of consumers.
Our geographic zones are as follows:
Zone 1 - San Francisco / New York City / Seattle
Zone 2 - Los Angeles / Washington DC / Austin / Boston / Sacramento / San Diego
Zone 3 - Atlanta / Portland / Chicago / Philadelphia / Denver / Miami / Dallas / Raleigh
Zone 4 - All other US cities
The base salary range listed for this full-time position excludes commission (if applicable), equity and benefits. The pay range shown on each job posting is the minimum and maximum target for new-hire salaries. Actual pay may be higher or lower depending on factors like skills, experience, and relevant education or training.
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Senior Machine Learning Engineer (Research Scientist) - Data Foundation & AI
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Senior Software Engineer - AI Applications
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Senior Software Engineer - Data Infrastructure
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Experienced Engineering Manager, Network Enablement and Access (NEA)
- See role
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FinOps Program Manager
- See role
Seattle, WA
Integrations Operations Program Manager
- See role
Seattle, WA
Senior Data Scientist - Data Foundations & AI
- See role
Seattle, WA
Senior Data Scientist - Fraud
- See role
Seattle, WA
Senior Developer Relations Engineer - Customer Growth and Experience
- See role
Seattle, WA
Senior Machine Learning Engineer - Payments
- See role
Seattle, WA
Senior Machine Learning Engineer (Research Scientist) - Data Foundation & AI
- See role
Seattle, WA
Senior Software Engineer - Backend
- See role
Seattle, WA
Senior Software Engineer - Data Infrastructure
- See role
Seattle, WA
Senior Software Engineer - Fullstack
- See role
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Software Engineer
- See role
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Staff Software Engineer - Online Storage
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Senior Developer Relations Engineer - Customer Growth and Experience
