Senior Data Engineer

2 weeks ago


San Francisco, United States UpRecruit Full time

Job Details:

  • Title: Sr. Data Engineer
  • Salary: $180-$230K
  • Requirements: 8+ years of software dev exp (Large Data Sets or Big Data)
  • Location: 100% onsite (San Francisco Bay Area)
Our client, a gaming startup, is seeking a Sr. Data Engineer to join their passionate team. The ideal candidate is an experienced engineer who will play a vital role in reconstructing and refining data processes, collaborating closely with the engineering team to guarantee smooth integration of data solutions.

Responsibilities
  • Comprehend and optimize existing data processes within Databricks.
  • Collaborate with the engineering team to seamlessly integrate data solutions.
  • Translate basic product requirements into robust back-end systems.
  • Demonstrate proactive implementation of solutions to meet project deadlines.
  • Work on systems involving various stakeholders, requiring effective communication skills.
  • Provide technical leadership and guide the team on coding best practices, data management, and system architecture.
Requirements
  • Bachelor's or Master's degree in Computer Science, Software Engineering, or related field.
  • Senior Back-End Engineer experience with focus on data-related projects.
  • Proficiency in various data storage solutions including basic RDBMS, key-value stores, data warehouses, and data lakes.
  • Familiarity with caching systems.
  • Extensive experience in at least one queue system such as Kafka, RabbitMQ, or similar (understanding of enterprise solutions like Confluent or MSK is a plus).
  • Basic understanding of open-source technologies in data pipelines, such as Airbyte or Meltano.
  • Exposure to enterprise solutions like Fivetran or Databricks is advantageous.
  • Real-time data processing and streaming techniques using Spark structured streaming and Kafka.
  • Ability to work independently, architect solutions, and perform data ingestion development and support.
  • Segregation capability between BI analytics and data engineering workflows.


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