Staff Data Engineer
Company | Kandji |
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Location | Miami, FL, USA |
Salary | $Not Provided – $Not Provided |
Type | Full-Time |
Degrees | |
Experience Level | Senior, Expert or higher |
Requirements
- 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
Responsibilities
- 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.
Preferred Qualifications
- 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)