DataOps Engineer

Position Name: DataOps Engineer

Location: Long Beach CA 90802

Job Description:

The DataOps Engineer will be responsible for enhancing and managing the data infrastructure and processes to support datadriven decisionmaking across the organization. This role involves collaborating with data engineering analytics and IT teams to streamline data workflows ensure data quality and implement efficient data operations practices.

Key Responsibilities:

1. Data Pipeline Management:
   

   • Design implement and maintain scalable and reliable data pipelines for extracting transforming and loading (ETL) data from various sources.
     
   • Optimize data workflows for performance and scalability.
     

2. Automation and Monitoring:
   

   • Develop and automate data workflows and monitoring systems to ensure data availability accuracy and timely delivery.
     
   • Implement and maintain monitoring solutions to track data pipeline health and performance.
     

3. Data Integration:
   

   • Integrate data from multiple sources including databases APIs and thirdparty services.
     
   • Ensure seamless data integration and synchronization across platforms.
     

4. Data Quality and Governance:
   

   • Establish and enforce data quality standards and processes.
     
   • Implement data governance practices to ensure data integrity and compliance.
     

5. Collaboration and Support:
   

   • Work closely with data engineers data scientists and business analysts to understand data requirements and deliver solutions.
     
   • Provide technical support and troubleshooting for datarelated issues.
     

6. Documentation and Best Practices:
   

   • Document data processes workflows and architecture.
     
   • Develop and promote best practices for data management and operations.
     

Skills and Experience Required:

• Technical Expertise:
  

  • Strong experience with data engineering ETL processes and data pipeline management.
    
  • Proficiency in SQL and scripting languages (e.g. Python Bash).
    
  • Experience with data orchestration tools (e.g. Apache Airflow Luigi).
    
  • Knowledge of data warehousing solutions (e.g. Snowflake Redshift BigQuery).
    

• Tools and Technologies:
  

  • Experience with cloud platforms (e.g. AWS Azure GCP) and their data services.
    
  • Familiarity with containerization and orchestration tools (e.g. Docker Kubernetes).
    

• Data Management:
  

  • Understanding of data modeling data integration and data quality frameworks.
    
  • Experience with version control systems (e.g. Git).
    

• Soft Skills:
  

  • Strong problemsolving and analytical skills.
    
  • Excellent communication and collaboration abilities.
    
  • Ability to work independently and manage multiple tasks simultaneously.
    

Highly Desired:

• Experience with DataOps practices and tools.
  
• Familiarity with machine learning workflows and tools.
  
• Certification in relevant technologies or platforms.