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Build and operate a global renewable-energy data platform, engineering pipelines and AI-ready datasets on Azure/Microsoft Fabric to power analytics and ML at scale.
Build and scale AI platforms that integrate LLM agents with lab systems, enabling scientists to co-drive research through full-stack services, APIs, and cloud infrastructure.
Build and orchestrate autonomous AI agents that reason, plan, and execute workflows using Hermes Agent and MCP, integrating tools and memory systems for production-grade applications.
Design and maintain scalable ETL pipelines, data warehouses, and real-time streaming solutions using SQL, Python, and cloud platforms like AWS/Azure/GCP.
Build and maintain scalable data pipelines and warehouses for analytics and ML, integrating multiple sources using Python, SQL, and cloud tools.
Build and deploy AI agents for fintech workflows (risk, fraud, payments) and the platform that powers them, including orchestration, tooling, and safety guardrails.
Lead the design and optimization of ML algorithms in Vertex AI, build scalable data pipelines, and mentor engineers to productionize personalization and recommendation systems for a global gaming commerce platform.
Builds and automates data pipelines for audit teams using Python, SQL, DBT, Prefect, and Airflow on modern cloud platforms.
Senior Data Engineer builds and maintains AWS-based data pipelines and cloud-native workflows to deliver trusted, scalable data solutions for product teams and analytics at a global telecom leader.
Build a backend workflow engine in Python (FastAPI) and a React/TypeScript UI to let scientists run simulations without touching HPC clusters; own the full stack from design to deployment.
Senior engineer building and operating the AI platform that deploys, secures, and governs responsible agentic AI systems using Kubernetes, Terraform, and cloud services.
Build and optimize scalable data pipelines for a transparent, onchain trading platform, using IaC and modern data tools to enable real-time analytics and AI-driven insights.
Build and own Zefir’s data platform: a canonical semantic layer, governed metrics, and self-serve access so Finance, Growth and Ops can trust their KPIs and AI agents can query safely.
Build and maintain data pipelines and dbt models in Redshift to turn raw payments data into clean, tested, and self-serve analytics for Flutterwave’s fintech platform.
Design and build scalable data pipelines and lakehouse/warehouse architectures to power analytics, dashboards, and AI models using AWS, Databricks, and Snowflake.
Build and secure full-stack financial platforms, including React/TypeScript front ends, Node.js/Java/Python backends, and MuleSoft API gateways, while ensuring compliance with financial regulations.
Build and maintain data pipelines, internal tools, and cloud infrastructure for CRISPR gene-editing research, using Python, AWS, and React.
Build and scale an AI-powered healthcare platform that unifies clinical intelligence and value-based care workflows using full-stack development and cloud-native infrastructure.
Build production-grade AI systems and data pipelines end-to-end, owning schema design, ETL, FastAPI/Next.js apps, and cloud deployments on AWS/Azure.
Build and maintain the data warehouse, semantic layer, and quality pipelines that power Stand’s AI-driven risk engine and underwriting decisions, migrating from Postgres to a scalable analytics platform with dbt, orchestration, and reconciliation.
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