Senior Data Engineer
UpRecruit
San Francisco, california
Job Details
Full-time
Full Job Description
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.