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 maintain Zendesk’s globally distributed data platform using AWS, Spark, Flink, and Kubernetes to power customer-facing analytics and ML initiatives.
Build and scale ad-tech data infrastructure that processes billions of events daily, transforming raw ad server and SSP/DSP data into real-time analytics for campaign optimization and business intelligence.
Designs and builds scalable data pipelines and warehouses using cloud tools (AWS/Azure), SQL/NoSQL, and big-data frameworks (Spark, Kafka) to enable analytics and ML for clients.
Senior Data Engineer builds high-performance data pipelines and lakehouse architecture using ClickHouse, Postgres, and open-source tools to power real-estate analytics and products.
Build and maintain GCP-based data pipelines (batch/streaming) for analytics and ML, using BigQuery, Dataflow, Pub/Sub, Kafka, and ClickHouse.
Build real-time banking platform features using Java, Kafka, Flink, and Azure; lead agile teams and enforce engineering best practices in a Swiss bank’s Digital Core.
Principal Data Engineer builds and scales AI-native data infrastructure for LLM-powered security products, including RAG and agentic systems at Exabyte scale.
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.
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