Sr./Staff Data Engineer

Firework is building data systems that support analytics, machine learning, and data-driven product decisions at scale. This hybrid role in the Bay Area focuses on designing and operating the core data infrastructure, from event ingestion and stream processing to warehouse-backed pipelines that keep teams moving quickly and reliably.

As a Sr./Staff Data Engineer, you will partner with data and analytics experts to improve end-to-end processing, troubleshoot production issues, and help set engineering standards. You will also provide technical mentorship to other data engineers while advancing best practices across distributed data systems.

Role scope

• Design, develop, and implement backend and machine learning data infrastructure, including event-based ingestion, stream processing, data warehousing, pipelines, and analytics applications
• Build analytics tools that leverage the data pipeline for actionable insights across customer acquisition, operational efficiency, and other key business metrics
• Create distributed data pipelines for ETL, feature engineering, and model running, and develop/maintain these workflows in production
• Develop data tooling that supports data analysts and data scientists in building and optimizing Firework’s product
• Ensure data separation and security across national boundaries using multiple data centers and AWS regions
• Collaborate on data system functionality and take ownership of end-to-end data processing, including troubleshooting, diagnosis, performance benchmarking, load balancing, and code reviews
• Mentor other data engineers by providing technical guidance, sharing best practices, and supporting professional growth

Requirements

• 5+ years of professional experience in data engineering, software engineering, or a closely related field, with significant experience designing and maintaining production data or machine learning systems
• Strong proficiency in Python and SQL, including advanced querying, data transformations, and performance optimization
• Experience building and maintaining large-scale ETL/ELT pipelines and distributed data processing systems
• Hands-on experience with modern data warehousing technologies such as Snowflake, BigQuery, or open table formats such as Iceberg
• Experience with data processing frameworks such as Apache Spark, Flink, or equivalent technologies
• Familiarity with workflow orchestration tools such as Apache Airflow, Dagster, or Prefect
• Experience with cloud infrastructure, preferably AWS or GCP
• Strong understanding of data modeling, database design, and data architecture principles
• Experience implementing data quality, monitoring, and reliability practices in production environments
• Strong analytical and problem-solving skills with the ability to independently drive complex technical projects
• Excellent communication and collaboration skills across technical and non-technical teams
• Leadership potential and interest in growing into a people management track, including mentoring and driving technical strategy

Technologies

• Python, SQL, Snowflake, BigQuery, Iceberg
• Apache Spark, Flink
• Apache Airflow, Dagster, Prefect
• AWS, GCP

Location

• San Mateo, CA (hybrid)
• Bay Area candidates are preferred

Compensation

• Estimated pay range: $160,000 - $180,000 per year
• Stock options may also be included and can affect total compensation
• The posted range reflects the anticipated low and high end and may change based on business needs
• Starting pay is determined using factors including primary work location, evaluation of skills and experience, market demands, and internal parity