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Urgent! Data Engineer (AI/Analytics Pipeline) Job | Wakapi
We are passionate about what we do and we strive to be better with each day that goes by.
We want to contribute to the generation of a technological community powered by the conviction that, through small actions, we can help create a better world.
The Role:
We are looking for a motivated and intellectually curious Data Engineer to join our growing Data Science and Solutions team.
This role is ideal for someone passionate about AI, data integration, and building modern data infrastructure.
You will play a key role in scaling and optimizing our AI and analytics platform by developing robust, secure, and scalable data pipelines in Databricks on AWS.
You’ll collaborate closely with AI/ML experts, backend and frontend engineers, and product stakeholders to transform data into impactful insights and intelligent user experiences.
If you're eager to work in a dynamic, remote-first environment where your contributions directly influence real-world outcomes, we want to hear from you.
Responsibilities:
Data Pipeline Development
- Design, build, and maintain ETL/ELT pipelines in Databricks to ingest, clean, and transform data from a variety of sources.
- Develop gold layer tables in a Lakehouse architecture to support machine learning models and real-time APIs.
- Monitor data quality, lineage, and reliability leveraging Databricks best practices and observability tools.
AI-Driven Data Access Enablement
- Collaborate with AI/ML teams to structure and model data for natural language prompts, semantic retrieval, and vector search using Unity Catalog metadata.
- Contribute to the development of data interfaces and agent tools for secure, role-based access to structured and unstructured data.
API & Serverless Backend Integration
- Partner with backend engineers to create serverless APIs (e.g., AWS Lambda + TypeScript) that expose curated data for front-end applications.
- Implement scalable, secure, and performant APIs with a strong focus on data governance and compliance.
- Develop infrastructure-as-code and monitoring frameworks to support multi-tenant scaling of pipelines and AI endpoints.
Requirements:
Experience with AWS Lambda (Node.js/TypeScript) and API Gateway or other serverless frameworks.
Understanding of API design principles and familiarity with RESTful and/or GraphQL endpoints.
Exposure to React-based frontend architectures and awareness of how backend data delivery impacts UI/UX performance.
Experience with A/B testing, experimentation frameworks, and logging for model inference and user analytics.
C - NV - 28072025
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Unlock Your Data Engineer Potential: Insight & Career Growth Guide
Real-time Data Engineer Jobs Trends in Mendoza, Argentina (Graphical Representation)
Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph below. This graph displays the job market trends for Data Engineer in Mendoza, Argentina using a bar chart to represent the number of jobs available and a trend line to illustrate the trend over time. Specifically, the graph shows 68473 jobs in Argentina and 1426 jobs in Mendoza. This comprehensive analysis highlights market share and opportunities for professionals in Data Engineer roles. These dynamic trends provide a better understanding of the job market landscape in these regions.
Great news! Wakapi is currently hiring and seeking a Data Engineer (AI/Analytics Pipeline) to join their team. Feel free to download the job details.
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An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Wakapi adheres to the cultural norms as outlined by Expertini.
The fundamental ethical values are:The average salary range for a Data Engineer (AI/Analytics Pipeline) Jobs Argentina varies, but the pay scale is rated "Standard" in Mendoza. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.
Key qualifications for Data Engineer (AI/Analytics Pipeline) typically include Computer Occupations and a list of qualifications and expertise as mentioned in the job specification. Be sure to check the specific job listing for detailed requirements and qualifications.
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Before the Interview:To prepare for your Data Engineer (AI/Analytics Pipeline) interview at Wakapi, research the company, understand the job requirements, and practice common interview questions.
Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Wakapi's products or services and be prepared to discuss how you can contribute to their success.
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