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Build and maintain scalable data pipelines and transformations using Python, SQL, dbt, and Snowflake to power BI, analytics, and AI initiatives in a modern DataOps environment.
Principal Data Engineer designs and builds secure, scalable data platforms for national-scale genomics and healthcare research, using Python, SQL, and cloud infrastructure.
Designs and builds cloud-based ELT/ETL pipelines on AWS/Azure and Databricks to integrate financial, ERP, and operational data for a renewable-energy IPP, then delivers Power BI reports for executives and investors.
Build and operate PayPay’s AWS-based data infrastructure using Terraform and Databricks, ensuring reliability, security, and smooth data workloads for the fintech platform.
Lead the AI and data platform for a live-commerce marketplace, building pipelines, personalization, and automation systems that power buyer experiences, seller tools, and marketing campaigns using Python, ClickHouse, and LLMs.
Build and maintain AI-powered search infrastructure for a learning platform, designing Elasticsearch pipelines, hybrid retrieval systems, and backend services to deliver low-latency, high-relevance results at scale.
Builds and optimizes a large-scale Earth Observation data pipeline processing satellite radar data, focusing on scalability, performance, and integration with scientific algorithms using Python, HPC, and cloud tools.
Build and maintain data pipelines with Estuary and dbt, write SQL and Python on Amazon Redshift to transform raw data into clean, tested datasets for analytics at Flutterwave.
Lead AI Engineer builds and architects AI-driven solutions, prototypes with LLMs and GenAI frameworks, and sets engineering standards for scalable, secure, and cost-efficient AI applications.
Build and deploy enterprise-grade AI agents and RAG pipelines, orchestrating multi-step reasoning systems with robust governance and observability on GCP or AWS/Azure.
Senior Data Engineer builds and maintains automated data pipelines in Python, integrating with Snowflake and ServiceNow to ensure reliable data flow and system observability.
Build and own AI agent infrastructure and automation systems that connect LLMs to internal tools and data, enabling self-service workflows for marketing and sales teams using Python, JavaScript, and GCP serverless services.
Build Python data pipelines that fuse satellite imagery, AIS vessel tracking, and RF signals into a real-time maritime intelligence platform for defense and environmental monitoring.
Build and scale high-performance ML systems for real-time fraud detection using PyTorch/TensorFlow and multi-GPU training pipelines, while mentoring engineers and shaping data architecture.
Build and maintain Snowflake-based data pipelines and APIs that feed Finance reporting and analytics, using Python, SQL, Airflow, and dbt in a cloud-first AWS stack.
Build a distributed workflow engine and visual editor for scientists to run simulations without touching HPC clusters, using Python, FastAPI, React, and PostgreSQL.
Build and maintain a GCP-based data lake and Spark pipelines to process ride-hailing, delivery, and financial data, enabling AI/ML use cases and cross-team analytics.
Build and maintain high-throughput data pipelines for a credit-scoring platform, using Python, PySpark, SQL, and Airflow to process large volumes of financial data.
Builds and automates data pipelines on GCP and Snowflake using DBT, Prefect, and Airflow to support audit analytics at a global source-to-pay platform.
Builds and maintains ETL pipelines and data warehouses on GCP to feed AI-driven marketing systems, using Python, SQL, dbt, and Airbyte.
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