Data Engineer Los Angeles Dodgers
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.
- 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.
- 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.