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Full-Time

Data Engineer

Posted on 6/13/2024

Divergent

Divergent

Compensation Overview

$116.6k - $194.4kAnnually

+ Equity Plan + Incentive Bonus

Senior

Carson, CA, USA

Category
Data Engineering
Data & Analytics
Required Skills
Redshift
Python
NoSQL
Data Science
BigQuery
Apache Spark
SQL
Java
AWS
JIRA
Hadoop
Splunk
Oracle
Snowflake
Requirements
  • Bachelor’s or Master’s in computer science, mathematics, data science, data engineering, computational science, software engineering, or related fields.
  • 5+ years of experience in software development and data engineering.
  • Proven experience in data engineering, ETL, and data pipeline development.
  • Strong knowledge of SQL and relational databases.
  • Experience with Big Data technologies such as Hadoop, Spark, and NoSQL databases is a plus.
  • Familiarity with data warehousing concepts and tools (e.g., AWS Redshift, Google BigQuery, Snowflake, Microsoft Fabric) and data lakehouse architectures.
  • Solid understanding of data integration and data transformation techniques.
  • Experience with integrating with services like Jira, Splunk, Oracle, MES, ERP, and in-house web applications.
  • Strong proficiency in programming languages such as Python, Java, or Scala.
  • Familiarity with industry standards and regulations for data protection.
  • Deep understanding of software development processes and best practices.
  • Strong analytical and problem-solving skills, with the ability to identify and solve complex technical issues.
  • Strong project management skills and ability to manage multiple projects simultaneously.
  • Excellent communication and collaboration abilities.
  • Self-motivated with a passion for continuous learning and improvement.
  • Ability to work effectively with cross-functional teams, including business analysis, product management, engineering, and customer success.
Responsibilities
  • Design, develop, and maintain data pipelines and ETL processes.
  • Optimize and fine-tune data pipelines for performance and scalability.
  • Implement data quality checks and monitoring.
  • Develop and maintain data integration tools and frameworks.
  • Work on integrations with external services.
  • Lead the design and development of data engineering framework.
  • Develop and maintain software development best practices.
  • Collaborate with cross-functional teams.
  • Collaborate with data scientists and analysts.
  • Monitor industry data engineering and software development trends.

Company Stage

N/A

Total Funding

N/A

Headquarters

N/A

Founded

N/A

INACTIVE