Senior Data Engineer

Job not on LinkedIn

September 9

Apply Now

Receive Emails with Similar Jobs

Welocalize

WebsiteLinkedInAll Job Openings

Artificial Intelligence • Enterprise • SaaS

Welocalize is a leader in providing enterprise language services and AI-powered translation solutions. Known for its OPAL platform, Welocalize offers fit-for-purpose global content delivery, enabling stronger engagement and revenue for its clients. Specializing in AI-enabled service delivery, OPAL leverages machine translation engines and natural language processing to automate and optimize translations across various industries, including legal, medical, and technological sectors. Welocalize supports multiple content use cases such as marketing localization, software testing, and multilingual SEO, catering to a diverse range of industry needs. Additionally, Welocalize's commitment to AI innovation is emphasized by its new brand Welo Data, providing high-quality training data for AI development, further strengthening its position as a trusted partner for global enterprises.

1001 - 5000 employees

🤖 Artificial Intelligence

🏢 Enterprise

☁️ SaaS

📋 Description

• Design and build realistic toy/dummy datasets at varying complexity levels (simple, moderate, complex). • Ensure datasets reflect real-world scenarios while remaining clean, reproducible, and well-structured (CSV format). • Write concise, natural-language prompts (<40 words) tailored for business analysts. • Reproduce target visualizations with aesthetic and analytical fidelity. • Write clean, reproducible Python code using libraries like pandas, matplotlib, seaborn, and plotly. • Define correctness criteria tailored to open-ended insight prompts. • Provide supporting documentation with expected values and metrics (e.g., means, correlations, test results). • Rigorously check each example against quality rubrics (correctness, completeness, clarity, justification). • Maintain a high standard of accuracy across data, prompts, and visualizations.

🎯 Requirements

• 10+ years of professional experience in data engineering or applied data science. • Expert-level proficiency in Python (data wrangling, visualization, statistical testing). • Deep understanding of data modeling, prompt crafting, and reproducible workflows. • Exceptional attention to detail and quality control. • Proven success in high-impact technical environments. • English proficiency assessment and a Python skills test required.

🏖️ Benefits

• Part-time, flexible hours