Data Platform Engineer – IAAI

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Design, develop, and operationalize an agricultural data platform for AI-enabled research and deployment. Own end-to-end data pipelines for ingestion, processing, storage, and retrieval, including robust ETL/ELT for noisy, heterogeneous real-world datasets. Build and support core platform components such as databases, data lakes/lakehouse structures, APIs, and integration layers, while implementing validation, sanitization, and data quality checks. Collaborate with applied research scientists on governance, standards, and downstream modeling needs.

Location: Anywhere

Workplace: Remote

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Seniority: Mid level

Key Responsibilities

•Implement end-to-end data pipelines for ingestion, processing, storage, and retrieval aligned to platform architecture and design specifications.
•Develop and maintain ETL/ELT workflows for structured and semi-structured agricultural data from multiple sources.
•Contribute to core platform components including databases, data lakes, APIs, and integration layers; support secure, scalable storage and access.
•Implement data validation, sanitization, and quality checks, including schema enforcement, metadata management, and provenance tracking.
•Work with the Applied Research Scientist to translate governance requirements and designs into executable solutions, and document pipeline logic and operating procedures.

Key Requirements

•Bachelor’s degree in computer science, data engineering, information systems, software engineering, or a related field.
•2-4 years of progressive experience with HPC environments or advanced research computing systems.
•Experience building end-to-end data ingestion and ETL/ELT workflows.
•Ability to design scalable data lakes/lakehouse structures for mixed-structure datasets.
•Familiarity with at least one data engineering programming language (e.g., Python or Java) plus foundational knowledge of databases, data pipelines, or distributed systems.

Experience:2-4 yearsHigh-performance computing (HPC)Research computingData engineeringAgricultural data

Education:Bachelor's in computer science, data engineering, information systems, software engineering, or related field

Skills:Intellectual curiosityCollaborationDocumentationCode review feedback incorporationResponsible data handling

Tech Stack:PythonJavaETLELTData pipelinesData lakesLakehouseAPIsDatabasesData ingestionData processingWorkflow orchestrationData cataloguingMetadata managementSchema designProvenance trackingDistributed systemsCloudOn-premise

Company Brief

MBZUAI

Website

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MBZUAI

4 days ago

Data Platform Engineer – IAAI

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Location: Anywhere

Workplace: Remote

Employment Type: Full time

Job Function: DevOps, Cloud & Infrastructure

Seniority: Mid level

Key Responsibilities

•Implement end-to-end data pipelines for ingestion, processing, storage, and retrieval aligned to platform architecture and design specifications.
•Develop and maintain ETL/ELT workflows for structured and semi-structured agricultural data from multiple sources.
•Contribute to core platform components including databases, data lakes, APIs, and integration layers; support secure, scalable storage and access.
•Implement data validation, sanitization, and quality checks, including schema enforcement, metadata management, and provenance tracking.
•Work with the Applied Research Scientist to translate governance requirements and designs into executable solutions, and document pipeline logic and operating procedures.

Key Requirements

•Bachelor’s degree in computer science, data engineering, information systems, software engineering, or a related field.
•2-4 years of progressive experience with HPC environments or advanced research computing systems.
•Experience building end-to-end data ingestion and ETL/ELT workflows.
•Ability to design scalable data lakes/lakehouse structures for mixed-structure datasets.
•Familiarity with at least one data engineering programming language (e.g., Python or Java) plus foundational knowledge of databases, data pipelines, or distributed systems.

Experience:2-4 yearsHigh-performance computing (HPC)Research computingData engineeringAgricultural data

Education:Bachelor's in computer science, data engineering, information systems, software engineering, or related field

Skills:Intellectual curiosityCollaborationDocumentationCode review feedback incorporationResponsible data handling

Company Brief

MBZUAI

Website