Freelance Principal Data Engineer - Remote Mexico

Posted 2 days agoViewed

💎 Seniority level: Principal, 7+ years

🔍 Industry: Software Development

🏢 Company: Seamless.AI👥 501-1000💰 $75,000,000 Series A about 4 years agoSales Automation Artificial Intelligence (AI)Lead Generation Machine Learning Information Technology Software

🗣️ Languages: English, Spanish

⏳ Experience: 7+ years

Requirements:

Strong proficiency in Python and experience with related libraries and frameworks (e.g., pandas, NumPy, PySpark).

Hands-on experience with AWS Glue or similar ETL tools and technologies.

Solid understanding of data modeling, data warehousing, and data architecture principles.

Expertise in working with large data sets, data lakes, and distributed computing frameworks.

Experience developing and training machine learning models.

Strong proficiency in SQL.

Familiarity with data matching, deduplication, and aggregation methodologies.

Experience with data governance, data security, and privacy practices.

Strong problem-solving and analytical skills, with the ability to identify and resolve data-related issues.

Excellent communication and collaboration skills, with the ability to work effectively independently.

Highly organized and self-motivated, with the ability to manage multiple projects and priorities simultaneously.

Responsibilities:

Design, develop, and maintain scalable ETL pipelines to acquire, transform, and load data from various sources into the data ecosystem.

Work with stakeholders to understand data requirements and propose effective data acquisition and integration strategies.

Implement data transformation logic using Python and relevant frameworks, ensuring efficiency and reliability.

Utilize AWS Glue or similar tools to create and manage ETL jobs, workflows, and data catalogs.

Optimize ETL processes to improve performance and scalability, particularly for large datasets.

Apply data matching, deduplication, and aggregation techniques to enhance data accuracy and quality.

Ensure compliance with data governance, security, and privacy best practices within the scope of project deliverables.

Provide recommendations on emerging technologies and tools that enhance data processing efficiency.

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