Remote Data Jobs

• Drive the Monitoring & Evaluation (M&E) framework for the "IremboAI" initiative.
• Transform raw data into actionable insights to measure the project's success.
• Build and maintain production-grade data models using SQL/dbt.

• Play a pivotal role in transforming raw data into actionable insights that drive strategic decisions.
• Maintain accurate and accessible data pipelines while building automated dashboards and reports.
• Improve data integrity, governance, and usability for teams across the organization.

• Collaborate with cross-functional teams to translate business requirements into technical solutions.
• Implement MLOps practices like CI/CD pipelines and model deployment using appropriate tools and frameworks.
• Provide technical leadership by mentoring team members and contributing to technical discussions.

Responsible for managing data migration processes, identifying and resolving anomalies, and maintaining data integrity across systems. Working closely with cross-functional teams, you will support process improvements, communicate trends and insights, and contribute to a seamless user experience. Innovate on operational workflows and provide technical support during migrations.

Support data-driven decision-making by providing accurate reporting and data quality management. Work closely with internal teams and external partners to compile, analyze, and present data. Manage multiple projects and adapt to changing priorities.

• Design, develop, and maintain scalable data platform components for ingestion, transformation, and analytics.
• Build and scale data pipelines using tools such as Airbyte, Rudderstack, Kafka, and DBT with Snowflake.
• Implement CI/CD workflows with GitHub Actions and ensure robust observability using Datadog.

• Craft contextually accurate questions for AI training.
• Analyze SQL queries and result tables.
• Maintain linguistic quality and logical accuracy.

This role ensures clients receive technical support for SaaS solutions, focusing on data pipelines and integrations. Responsibilities include troubleshooting, optimizing data flows, and implementing solutions with SQL and Python. The role requires strong communication skills to explain complex issues and improve support processes through automation.

• Design, develop, and maintain scalable data pipelines for ingestion, parsing, filtering, and optimization of diverse datasets.
• Implement robust data modeling techniques to structure and format datasets for efficient training.
• Collaborate with researchers, engineers, and cross-functional teams to meet the evolving needs of AI models.

• Lead the design and implementation of cloud-based data architectures.
• Work with cross-functional teams to develop scalable, secure, and efficient data solutions.
• Influence data strategy, mentor team members, and provide architectural guidance to stakeholders.