Point your AI agent at freehire and let it find you a job. A CLI and an MCP server over the whole job API — no browser.
Build and optimize PySpark pipelines for large-scale data processing, using HDFS, YARN, and Spark SQL to deliver clean datasets for analytics and reporting.
Build and optimize PySpark pipelines for large-scale data processing, tuning performance and integrating with Hadoop, HBase, and SQL databases.
Build and maintain petabyte-scale storage infrastructure for AI training workloads, optimizing data pipelines and distributed systems for performance.
Build and maintain large-scale data pipelines and products for the App Store, processing petabytes daily to generate insights while ensuring privacy and correctness.
Build and optimize real-time and batch data pipelines for a fintech platform handling billions of events daily, using Spark, Kafka, and streaming frameworks to power fraud detection and AI products.
Leads the data engineering team to build scalable pipelines and data infrastructure for payments, risk, and product analytics using Iceberg, Kafka, Flink, Spark, Airflow, and AWS.
Leads data pipelines and platforms for payments, risk, and analytics using Iceberg, Kafka, Flink, Spark, and Airflow on AWS.
Build and maintain a privacy-focused data platform in Snowflake using dbt and Dagster, enabling accurate KPI tracking and analytics for a digital banking business.
Design and build scalable data pipelines and architectures for a fintech company, ensuring reliable data flow for analytics and financial products using Python, Spark, and cloud platforms.
Design and optimize data pipelines and models to support business decisions, using Java/Python/Scala and Snowflake/Spark/Flink.
Build and scale Relay’s Snowflake data warehouse and DBT models, create data tools and APIs, and ensure secure, privacy-preserving analytics for fintech growth.
Build and own the real-time data pipelines and infrastructure that feed AI models for a biotech platform, integrating customer systems and ensuring clean, reliable data at scale.
Principal Data Engineer builds and scales the data platform at JobGet, a mobile-first hiring platform, using Snowflake, dbt, Kafka, and real-time streaming to power AI-driven job matching and analytics.
Build and scale high-throughput data pipelines and infrastructure for Lime’s global micromobility fleet, enabling analytics, ML models, and real-time business intelligence using Python, SQL, Spark, and cloud tools.
Designs and maintains data pipelines and vector databases to feed AI systems with clean, real-time data for RAG and agent memory.
Build and maintain Amazon’s massive data warehouse and ETL pipelines to power supply-chain analytics and business intelligence used by thousands of users.
Build and maintain risk computation platforms using Java, Spring Boot, and Big Data tech to quantify and reduce exposure in capital markets.
Build and scale risk-computation platforms in Java/Spring, Kafka, and Big Data stacks to quantify and reduce TD Securities’ exposure across global markets.
Design, deploy, and maintain scalable Kubernetes-based data pipelines and CI/CD workflows using Terraform, Jenkins, and ArgoCD to ensure reliable, cost-efficient cloud operations.
Build and maintain the core data pipeline that unifies large, messy datasets into clean, training-ready assets for Udio’s generative audio models using BigQuery, Dataflow, and TFRecords.
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