Staff Data Engineer

Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field or equivalent practical experience
8+ years of experience in software engineering, data engineering, or a related field, with at least 3 years focused on data operations or data infrastructure
Strong knowledge of AWS or other public cloud platforms (e.g., Azure, GCP)
Hands-on experience with ETL/ELT, schema design, and datalake technologies
Hands-on experience with data orchestration tools like Dagster, Airflow, Prefect
Hands-on experience with CI/CD pipelines, Docker, Kubernetes, and infrastructure-as-code tools (e.g., Terraform, Cloud Formation)
Familiarity with various data and table formats (JSON, Avro, Parquet, Iceberg)
Skill in developing organized systems in highly unstructured settings
Strong SQL knowledge and experience optimizing for relational databases
Strong knowledge of Python for use in data transformation
Love of data and passion for building reliable data products

Lead the design and implementation of data pipeline solutions leveraging centralized data platform infrastructure
Collaborate with data scientists, engineers, product managers, and stakeholders to architect scalable solutions to Product and Engineering data workflows
Partner closely with producers of data across Simplisafe to develop understanding of data creation and meaning
Identify areas for improvement and contribute to centralized data platform
Build data pipelines for Core Engineering data
Manage data pipeline, orchestration, storage, and analytics infrastructure for Product and Engineering
Monitor performance and reliability of data pipelines, implementing solutions for scalability and efficiency
Design database schemas and optimize table structures to support query and usage patterns across Product and Engineering
Support data discovery, catalog, and analytics tooling
Implement and maintain data security measures and ensure compliance with data governance policies
Design and implement testing strategies and frameworks to ensure the accuracy, reliability, and integrity of data pipelines
Advocate for best practices in data engineering
Play a key role in the formation of our new team, contributing to the developing team norms, practices, and charter for new team

Experience using and managing data analytics, data quality, and data catalog tools
Familiarity with data streaming platforms like Kafka, Kinesis, or Spark
Experience with cost optimization strategies for cloud-based data infrastructure