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Data Engineer
Los Angeles Dodgers

EXPIRED

EXPIRED

Application Deadline Ended


Apply by Ended 9/9/2023

Data Engineer

Los Angeles Dodgers

Posted 7 months ago

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Location


Los Angeles, CA, USA

Job Type


Job Description

We are seeking a motivated Data Engineer to join our team. As a Data Engineer, you will work closely with all Business Analytics team members to design, implement, and maintain our data infrastructure, systems, and processes.

Essential Duties/Responsibilities:

  • Lead the design and development of data pipelines and ETL processes to extract, transform, and load data from various sources into our data warehouse.
  • Define critical initiatives across departments and lead the scoping of data requirements.
  • Weight the impact of potential data solutions on business outcomes. Then lead implementation to ensure efficient and scalable outcomes.
  • Maintain data models, data dictionaries, and schema definitions to ensure data consistency and accuracy.
  • Proactively seek opportunities to optimize and tune systems for performance, reliability, and scalability.
  • Develop a roadmap for organization-wide data governance policies, procedures, and standards to ensure data integrity and compliance with relevant regulations.
  • Define data infrastructure and tooling needs in tandem with other analytics team members.
  • Stay updated with industry trends and emerging technologies in the data engineering field and push our team to improve processes and enhance tools.

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Qualifications Required

  • Bachelor's degree in Computer Science, Information Systems, Mathematics, or a related field. Masters degree in similar field preferred.
  • Minimum two years’ work experience in data engineering or a similar field.
  • Ability to develop strong working relationships with stakeholders, using business knowledge to scope out data initiatives that can drive the business case for strategic initiatives.
  • Experience prioritizing project opportunities to ensure critical business needs are met.
  • Proficiency in Python.
  • Mastery of SQL and relational databases, such as PostgreSQL, MySQL, or Oracle.
  • Advanced knowledge of data pipelines and ETL processes.
  • Familiarity with cloud-based data platforms, such as AWS, Azure, or Google Cloud, is preferred.
  • Understanding of data modeling concepts and exposure to data modeling tools.
  • Strong problem-solving skills and the ability to analyze data-related issues.
  • Excellent communication and collaboration skills to work effectively with team members.
  • Consistent track record of optimally crafting and implementing cross-functional projects with a basic understanding of organizational structure, goals, and mission.

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