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.
About the job
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
SQL, Python, dbt, Airflow, Redshift, Snowflake, Databricks, Spark, Kafka, Data Pipelines
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