AI Data Engineer

Teleperformance USA • North Carolina, North Carolina • 3w ago

Category : Information Technology

About TP

Teleperformance is a global, digital business services company. We deliver the most advanced, digitally powered business services to help the world's best brands streamline their business in meaningful and sustainable ways.

With more than 500,000 inspired and passionate people speaking more than 300 languages, our global scale and local presence allow us to be a force of good in supporting our communities, our clients, and the environment.

Benefits of working with TP include:

Paid Training

Competitive Wages

Full Benefits (Medical, Dental, Vision, 401k and more)

Paid Time Off

Employee wellness and engagement programs

Teleperformance and You

Through a balanced high-tech and high-touch approach blended with deep industry and geographic expertise, we make people's lives simpler, faster, and safer. We help companies adapt quickly to changing needs, and are inspired to deliver only the best in all that we do. You will become a key contributor in making that happen.

Did you know that our Chief Client Officer started her career at Teleperformance as an agent and advanced to the pinnacle of the company? At Teleperformance, the sky is the limit!

Purpose

The AI Data Engineer designs, develops, and maintains robust data pipelines to support AI data services operations, ensuring smooth ingestion, transformation, and extraction of large, multilingual, and multimodal datasets. This role collaborates with cross-functional teams to optimize data workflows, implement quality checks, and deliver scalable solutions that underpin our analytics and AI/ML initiatives.

This position is 100% work at home.

Your Responsibilities

Data Pipeline Development: Create and manage ETL workflows using Python and relevant libraries (e.g., Pandas, NumPy) for high-volume data processing.

Data Optimization: Monitor and optimize data workflows to reduce latency, maximize throughput, and ensure high-quality data availability.

Collaboration: Work with Platform Operations, QA, and Analytics teams to guarantee seamless data integration and consistent data accuracy.

Quality Checks: Implement validation processes and address anomalies or performance bottlenecks in real time.

Integration & Automation: Develop REST API integrations and Python scripts to automate data exchanges with internal systems and BI dashboards.

Documentation: Maintain comprehensive technical documentation, data flow diagrams, and best-practice guidelines.

Qualifications

Education and Specific Training

Bachelor's degree in Computer Science, Data Engineering, Information Technology, or a related field.

Relevant coursework in Python programming, database management, or data integration techniques.

Work Experience

3-5 years of professional experience in data engineering, ETL development, or similar roles.

Proven track record of building and maintaining scalable data pipelines.

Experience working with SQL databases (e.g., MySQL, PostgreSQL) and NoSQL solutions (e.g., MongoDB).

Special Certifications (Non-Mandatory)

AWS Certified Data Analytics - Specialty, Google Cloud Professional Data Engineer, or similar certifications are a plus.

Technical Skills

Advanced Python proficiency with data libraries (Pandas, NumPy, etc.).

Familiarity with ETL/orchestration tools (e.g., Apache Airflow).

Understanding of REST APIs and integration frameworks.

Experience with version control (Git) and continuous integration practices.

Exposure to cloud-based data solutions (AWS, Azure, or GCP) is advantageous.

Soft Skills / Competencies

Communication Skills (verbal and written): 4

Planning and Organization: 4

Problem Solving: 5

Goal Orientation: 4

Proactivity: 4

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