AI Data Engineer
AI Data Engineer
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Job Description
Job Title: AI Data Engineer
Department: Data Engineering / AI Data Services
Location: Global
Reports to: VP of AI Ops
Contract: Permanent
Travel Requirements: No
Salary: Open Budget
JOB SUMMARY / OVERVIEW
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 crossfunctional teams to
optimize data workflows implement quality checks and deliver scalable solutions that
underpin our analytics and AI/ML initiatives.
KEY RESPONSIBILITIES AND ACCOUNTABILITIES
Data Pipeline Development: Create and manage ETL workflows using Python and relevant
libraries (e.g. Pandas NumPy) for highvolume data processing.
Data Optimization: Monitor and optimize data workflows to reduce latency maximize
throughput and ensure highquality 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
bestpractice guidelines.
MAIN JOB REQUIREMENTS
Education and Specific Training
Bachelors 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
35 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 (NonMandatory)
AWS Certified Data Analytics Specialty Google Cloud Professional Data Engineer or similar
certifications are a plus.
REQUIRED SKILLS
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 cloudbased 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
Team Collaboration / Customer Orientation: 4
Qualified Candidates should send CV to
Job Title: AI Data Engineer
Department: Data Engineering / AI Data Services
Location: Global
Reports to: VP of AI Ops
Contract: Permanent
Travel Requirements: No
Salary: Open Budget
JOB SUMMARY / OVERVIEW
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 crossfunctional teams to
optimize data workflows implement quality checks and deliver scalable solutions that
underpin our analytics and AI/ML initiatives.
KEY RESPONSIBILITIES AND ACCOUNTABILITIES
Data Pipeline Development: Create and manage ETL workflows using Python and relevant
libraries (e.g. Pandas NumPy) for highvolume data processing.
Data Optimization: Monitor and optimize data workflows to reduce latency maximize
throughput and ensure highquality 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
bestpractice guidelines.
MAIN JOB REQUIREMENTS
Education and Specific Training
Bachelors 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
35 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 (NonMandatory)
AWS Certified Data Analytics Specialty Google Cloud Professional Data Engineer or similar
certifications are a plus.
REQUIRED SKILLS
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 cloudbased 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
Team Collaboration / Customer Orientation: 4
Employment Type
Full Time
