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.
Senior Data Engineer builds and evolves a scalable enterprise Lakehouse platform using Python, PySpark, Databricks, and Azure services to power analytics and AI workloads.
Build and maintain scalable ETL/ELT pipelines and cloud-native data architectures using Python, Spark, and cloud platforms (AWS/Azure/GCP) to power analytics and ML for global clients.
Build and maintain cloud-based data platforms and pipelines using AWS/Azure/GCP, orchestration tools, and data processing services to enable scalable analytics and ML operations.
Build and optimize Python-based ETL/ELT pipelines to migrate on-prem MS SQL Server data into Databricks, ensuring data quality and performance for AI/ML projects.
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.
Senior Data Engineer builds scalable data pipelines in Databricks and PySpark, refactors legacy SQL logic, and designs Medallion architecture for a large insurance client’s cloud migration.
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.
Design and build scalable data pipelines and applications for regulatory reporting in a global investment bank, using Python, Databricks, Spark, and cloud tech.
Design and maintain a cloud-based lakehouse on AWS, building real-time ingestion pipelines with Kafka/Debezium and PySpark, and curating trusted analytics layers for fintech decision-making.
Build and maintain scalable data pipelines and ML feature stores for industrial intelligence, using Spark, Python, and Databricks to turn automotive and supply-chain data into real-time insights.
Designs and builds scalable cloud data pipelines and platforms using Azure, Databricks, PySpark, and SQL to process large datasets for financial clients.
Build and maintain scalable data pipelines on Azure using Databricks, Delta Lake, and PySpark to support banking analytics and reporting.
Design and build scalable cloud data platforms using Databricks, Python/PySpark, Delta Lake, and CI/CD for enterprise analytics and governance.
Build and maintain scalable data pipelines on Azure Databricks and Delta Lake, ensuring data quality and security for analytics and AI workloads.
Design and build scalable data pipelines and modern data platforms on Azure for enterprise clients, focusing on ETL/ELT, data modeling, and analytics to support AI and business intelligence initiatives.
Build and maintain secure, high-performance ETL pipelines on Azure Databricks and Data Factory that ingest financial data, shape it into trusted assets, and expose curated products for analytics and AI across TD Bank.
Build and own the data pipelines, ML feature stores, and inference APIs that power renewable-energy analytics at scale, integrating forecasts into a SaaS platform for wind, solar, hydro, and storage assets.
Designs and builds scalable Azure-based data pipelines and analytics solutions using Databricks, Data Factory, and Java/Python microservices.
Build and optimize Databricks-based data pipelines for mining analytics, ensuring data integrity and enabling self-service access across South American teams.
Lead the design and maintenance of Databricks-based ETL pipelines and data models for a fintech platform, transforming raw financial data into insights for investors and AI workloads.
We couldn't check your fit for this role — add a CV to your profile to see it next time.