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Firework is seeking a Senior/Staff Data Engineer to design, develop, and implement backend and machine learning data infrastructure. You will own the full data stack—event-based ingestions, stream processing, data warehouse, ETL pipelines, visualization, and analytics applications.
Key responsibilities include:
- Design and build analytics tools that provide actionable insights into customer acquisition, operational efficiency, and key business metrics
- Develop and maintain distributed data pipelines for ETL, feature engineering, and model execution
- Create data tools for analytics and data science teams to support product innovation
- Ensure data security and separation across national boundaries, multiple data centers, and AWS regions
- Collaborate with data and analytics experts on system functionality, troubleshooting, performance benchmarking, and load balancing
- Mentor other data engineers, providing technical guidance, sharing best practices, and supporting their professional development
This is a high-impact role that combines individual technical contribution with leadership responsibilities. You'll work on large-scale systems serving the entire organization and help grow the data engineering team.
Requirements:
- 5+ years of professional experience in data engineering, software engineering, or closely related field, with significant production data or ML systems experience
- 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 (Snowflake, BigQuery, or open table formats like Iceberg)
- Experience with data processing frameworks (Apache Spark, Flink, or equivalent)
- Familiarity with workflow orchestration tools (Apache Airflow, Dagster, 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
- Strong analytical and problem-solving skills with ability to independently drive complex technical projects
- Excellent communication and collaboration skills across technical and non-technical teams
- Demonstrated leadership potential and genuine interest in growing into people management, including mentoring, team building, and technical strategy
