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Plaid

Senior Data Engineer - Data Engineering

Builds and owns scalable SQL/Python data pipelines, golden datasets, and workflows using DBT, Airflow, Redshift for large-scale data (500TB+). Collaborates cross-functionally to enable data-driven decisions at Plaid. Requires 4+ years data engineering experience.

191k – 287kSan Francisco, CAData EngineeringHybrid4+ YOE
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About the role

Responsibilities

  • Understand 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 datasets.
  • Lead key data engineering projects that drive collaboration across the company.
  • Advocate for adopting industry tools and practices at the right time.
  • Own core SQL and Python data pipelines that power our data lake and data warehouse.
  • Deliver 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.
  • Experience building data models and data pipelines on top of large datasets (500TB to petabytes).
  • Value SQL as a flexible tool, comfortable with modern SQL data orchestration tools like DBT, Mode, and Airflow.
  • Experience with performant warehouses and data lakes: Redshift, Snowflake, Databricks.
  • Experience building and maintaining batch and realtime pipelines using Spark, Kafka.
  • Appreciation for schema design, evolving analytics schema on top of unstructured data.
  • Excited to try new technologies, produce proof-of-concepts balancing technical advancement and adoption.
  • Get deep into managing, deploying, and improving low-level data infrastructure.
  • Empathetic with stakeholders, listen and collaborate on solutions balancing infra and business needs.
  • Champion for data privacy and integrity.

Skills

SQLPythondbtAirflowRedshiftSnowflakeDatabricksSparkKafkaData Pipelines

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