Staff Data Engineer

8+ years of strong data engineering design/development experience in building large-scale distributed data platforms/products
Advanced knowledge of Python, SQL
Familiarity with Apache Kafka, or Kinesis
Proficiency with dbt and data modeling, especially incremental models
Experience architecting and implementing data ingestion platforms, interacting with multiple third-party data sources, and assembling them into actionable structures
Experience in technical leadership for data architectures within greenfield efforts
Experience with both structured and unstructured datasets
Deep experience with workflow management systems (Airflow, Argo Workflows, etc)
Ability to establish and maintain relationships with key stakeholders

Lead the design and implementation of scalable, resilient data architectures that support current and future business needs without over-engineering.
Drive strategic initiatives to identify and eliminate inefficiencies in data collection and processing workflows, ensuring performance, reliability, and maintainability at scale.
Partner with cross-functional stakeholders to understand data needs and lead the planning of complex, cross-team technical initiatives.
Design and implement robust data observability practices, including usage metrics and monitoring systems to ensure the health and reliability of the data platform.
Work closely with engineers across teams to design efficient data storage and collection systems, with a strong emphasis on Privacy by Design principles.
Champion innovation by evaluating and adopting emerging technologies, tools, and best practices that improve data engineering workflows.
Mentor data engineers and empower data platform users by promoting best practices and maximizing the value of the platform’s capabilities.

Experience with a Security related SaaS product
Familiarity with applying Data Science algorithms and/or ML ops
Experience with a variety of data serialization formats (Avro, Parquet, JSON, Protobuf, etc)