Job Description

Note: This position does not offer any Visa sponsorship. We are only looking for applicants who are either local to Los Angeles, CA, or ready to relocate to the employers location.

Job Summary: Our Client is looking for a skilled Data Engineer to join their team. The ideal candidate will be responsible for designing, implementing, and maintaining data pipelines that ensure efficient and reliable data flow across our systems. You will work closely with data scientists, analysts, and other stakeholders to support data-driven decision-making processes.

Key Responsibilities:

• Design, develop, and maintain scalable and efficient data pipelines.
• Integrate, clean, and organize raw data from various sources into structured formats.
• Develop and maintain data warehouses and data lakes to support analytics and business intelligence needs.
• Implement and manage ETL (Extract, Transform, Load) processes to ensure data quality and consistency.
• Optimize database performance and query execution.
• Collaborate with data scientists and analysts to understand data requirements and deliver solutions.
• Ensure data security and compliance with relevant data protection regulations.
• Monitor and troubleshoot data-related issues and provide timely resolutions.
• Document data engineering processes, architectures, and workflows.

Qualifications:

• Bachelors degree in Computer Science, Information Technology, or a related field.
• Proven experience as a Data Engineer or in a similar role.
• Strong proficiency in SQL and experience with relational databases (e.g., MySQL, PostgreSQL, Oracle).
• Familiarity with big data technologies such as Hadoop, Spark, and Kafka.
• Experience with data integration tools and platforms (e.g., Talend, Apache NiFi).
• Proficiency in programming languages such as Python, Java, or Scala.
• Knowledge of cloud-based data solutions (e.g., AWS, Azure, Google Cloud Platform).
• Strong problem-solving and analytical skills.
• Excellent communication and teamwork abilities.

Preferred Skills:

• Experience with data warehousing solutions (e.g., Amazon Redshift, Google BigQuery).
• Familiarity with containerization and orchestration tools (e.g., Docker, Kubernetes).
• Knowledge of data governance and data privacy regulations.
• Certification in data engineering or related fields.

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