Senior Data Engineer

Remofirst

Senior Data Engineer responsible for designing and operating a cloud-native data platform for AI analytics. Collaborates with AI engineers to support LLM applications, agent-based systems, and RAG solutions.

Posted 7/24/2026full-timeRemote • 🇪🇬 EgyptSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and maintaining scalable data pipelines and infrastructure, with a strong focus on cloud platforms and modern data engineering tools. Capable of collaborating across teams to deliver high-quality data solutions that meet evolving business and AI requirements.

Highest-signal resume keywords

Data EngineeringPython ProgrammingSQL ProficiencyCloud Platforms (AWS)Dimensional Data Modeling

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Pipeline DevelopmentDimensional Data ModelingSemantic Data ModelsData Schema DesignVersion Control WorkflowsData Infrastructure ManagementCloud Services (S3, Redshift, Athena, Glue, Lambda)Data Engineering Tools (dbt, Airflow, Prefect)AI Architecture FamiliarityMonitoring and Orchestration

Soft Skills

Effective CommunicationCollaborationOwnership MindsetAdaptabilityProblem-Solving

Industry Keywords

Data SolutionsAnalyticsAI WorkloadsData ProductsStartup Environment

Tech Stack

Tools & technologies

AirflowAmazon RedshiftAWSCloudPythonSQL

About the role

Key responsibilities & impact

Design, build and maintain scalable data pipelines using modern data engineering tools (e.g., dbt, Airflow, Prefect).
Develop and maintain dimensional and semantic data models to support analytics and operational use cases.
Build curated data products that support analytics and modern AI workloads.
Design data schemas and storage strategies optimized for both analytical and AI workloads.
Build and maintain version control workflows and isolated development/test environments.
Manage and optimize cloud-based data infrastructure ensuring performance, scalability, reliability and cost efficiency.
Contribute to the architecture and evolution of the organization's modern data platform.
Collaborate closely with AI, Analytics, and Product teams to deliver scalable, high-quality data solutions.

Requirements

What you’ll need

5+ years of hands-on experience in Data Engineering with proven delivery in production environments.
Strong expertise in building scalable data pipelines using Python and SQL.
Hands-on experience with modern data engineering tools such as dbt, Airflow, Prefect, or similar.
Strong experience with dimensional data modeling and semantic data models.
Experience working with cloud platforms (AWS preferred), including services such as S3, Redshift, Athena, Glue, and Lambda.
Hands-on experience designing, building and operating modern data infrastructure, including storage, compute, orchestration, and monitoring.
Familiarity with modern AI architectures and the data requirements for LLMs, AI agents and RAG applications.
Strong ownership mindset with the ability to thrive in a fast-paced startup environment.
Ability to translate evolving business, analytics and AI requirements into scalable data solutions.
Effective communicator who collaborates well across Data, AI, Product, and Engineering teams.
A senior engineer who balances architectural thinking with hands-on execution.

Benefits

Comp & perks

Competitive compensation
100% remote work
PTO regulated by local statutory