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Firework
Firework
201 – 500 Employees
H1B Visa SponsoreCommerceMarketingVideo Commerce
Firework is a video commerce company helping retailers and eCommerce brands create more interactive digital shopping experiences. Its platform combines AI with video tools such as AI virtual assistants, digital showrooms, one-to-one virtual shopping, and shoppable video. Firework also provides global video infrastructure designed for fast, secure delivery and high data-privacy standards, supporting brands that want to connect richer content with customer engagement and online sales.
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Senior Data Engineer at Firework (Hybrid, California)

Senior Data Engineer responsible for scalable data infrastructure, machine learning pipelines, and analytics systems at Firework. The role supports the company’s AI, video commerce, and product initiatives.

USUnited StatesCACalifornia
$160,000 – $180,000 / year
HybridFull-timeSeniorEnglish RequiredData Engineer
AirflowApacheAWSBigQueryCloudETLGoogle Cloud PlatformPythonSparkSQL

Description

  • Architect and deliver backend and machine learning data infrastructure spanning event ingestion, stream processing, warehousing, pipelines, visualization, analytics, and applications.
  • Develop analytics tools that generate actionable insights into customer acquisition, operational efficiency, and business performance.
  • Build and operate distributed ETL, feature engineering, and model execution pipelines.
  • Create data products that enable analytics and data science teams to improve Firework’s product.
  • Maintain secure data separation across national boundaries using multiple data centers and AWS regions.
  • Partner with data and analytics specialists to strengthen data platforms and end-to-end processing.
  • Investigate technical issues, assess performance, balance workloads, and participate in code reviews.
  • Mentor data engineers, offer technical direction, share proven practices, and support career growth.
  • Provide technical leadership, shape architecture decisions, and help define engineering standards.

Requirements

  • At least five years of professional experience in data engineering, software engineering, or a related discipline, including substantial work with production data or machine learning systems.
  • Advanced proficiency in Python and SQL, including complex queries, data transformation, and performance tuning.
  • Experience developing and operating large-scale ETL or ELT pipelines and distributed processing systems.
  • Practical experience with modern data warehouses such as Snowflake or BigQuery, or open table formats such as Iceberg.
  • Experience using Apache Spark, Flink, or comparable data processing frameworks.
  • Working knowledge of orchestration platforms such as Apache Airflow, Dagster, or Prefect.
  • Experience with cloud infrastructure, preferably AWS or Google Cloud Platform.
  • Strong foundations in data modeling, database design, and data architecture.
  • Experience establishing data quality, observability, and reliability practices in production.
  • Strong analytical and problem-solving ability, with a track record of independently leading complex technical work.
  • Clear communication and collaboration skills across technical and non-technical teams.
  • Leadership potential and interest in progressing toward people management through mentoring, team building, and technical strategy.

Benefits

  • Stock options.
  • Compensation may be adjusted according to work location, skills, experience, market conditions, and internal equity.

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