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 optimizes large-scale ETL/ELT pipelines using Python, PySpark, SQL, and AWS services to deliver reliable, high-performance data solutions for global clients.
Design and build cloud data pipelines in AWS using PySpark and AWS Glue to process and transform data for analytics and reporting.
Build and maintain scalable full-stack apps with Python/FastAPI backend and React/TypeScript frontend, deploying on AWS and Kubernetes while integrating data pipelines and AI features.
Build and maintain data pipelines, warehouses, and governance for an insurance-focused platform using Python, Databricks/Snowflake, and cloud services.
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.
Design and migrate on-prem data pipelines to AWS using Glue, Redshift, EMR, and Python; automate workflows with Airflow and monitor with CloudWatch/Kibana.
Build and maintain AWS serverless pipelines: Glue ETL, Lambda integrations, DynamoDB writes, API Gateway endpoints, and CI/CD with CDK and Git.
Build and optimize Amazon’s cloud-based data infrastructure, designing ETL/ELT pipelines and reporting solutions to enable real-time analytics for IT services across the company.
Design and maintain scalable data pipelines using Python, SQL, Databricks, Snowflake, and cloud tools; lead a team of data engineers to deliver AI-driven marketing solutions.
Build and maintain scalable data pipelines and warehouses for Frostbite’s quality-engineering telemetry, enabling ML and engineering teams to analyze game-creation data efficiently.
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.
Build and maintain Amazon’s massive data warehouse and ETL pipelines to power supply-chain analytics and business intelligence used by thousands of users.
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 optimize both applications and data pipelines using Java, Python, JavaScript, and ETL tools to deliver scalable solutions.
Builds and maintains AWS-based data pipelines for ecommerce integrations, including SAP and marketplace APIs, using AWS Glue and DataOps practices.
Build and maintain data pipelines and analytics systems using Python, Snowflake, dbt, and AWS services for a fintech platform.
Lead the design and delivery of Barclays' Enterprise Data Platform, focusing on data lineage and quality to ensure end-to-end visibility of data flows across a complex cloud ecosystem.
Build and maintain cloud data pipelines and datasets to track cloud costs, usage, and performance for engineering and finance teams using AWS, Snowflake, and Python.
Design and build scalable data architectures on AWS Redshift and Glue, model semantic layers, and lead ETL pipelines for clients across multiple products.
Design and deploy production-grade GenAI and ML solutions on AWS, optimizing cost, security, and performance while embedding reusable patterns into DoiT’s Cloud Intelligence platform.
We couldn't check your fit for this role — add a CV to your profile to see it next time.
