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Senior Software Engineer builds and maintains distributed backend services in Java (with Python/Go) for SentinelOne’s AI-native cybersecurity platform, focusing on reliability, performance, and threat-analysis dashboards.
This role involves designing, building, and maintaining scalable Azure-based data pipelines and ETL solutions using Python, T-SQL, Azure Databricks, and Azure Data Factory. The engineer will also focus on data warehouse modeling, performance optimization, and implementing CI/CD pipelines within an on-site contract environment.
Sr. Data Engineer ( Delta-to-Iceberg Migration) Remote 12 Months Must Have skills: Hands-on data engineer with strong Python skills and experience building large scale Apache Spark pipelines on AWS. Deep platform…
Lead the design and development of enterprise data and analytics platforms on Azure, acting as a technical SME to deliver reporting and insights for Transport for NSW.
Data Engineer leading Microsoft Fabric and Azure data platform modernization in Brisbane—responsible for end-to-end data platform ownership, governance, and delivery across Azure Synapse, Data Lake, Power BI, and integration tools.
Build and maintain data models, pipelines, and dashboards to support analytics and reporting for DoorDash's logistics platform in São Paulo, using SQL, Python, and Snowflake.
Build and maintain data models, pipelines, and dashboards to support analytics and reporting for DoorDash's logistics platform, using SQL, Python, and Snowflake.
Builds and maintains data models, pipelines, and dashboards to support analytics and reporting for DoorDash’s logistics platform, using SQL, Python, and Snowflake.
Builds and maintains data pipelines, metrics, and dashboards to enable data-driven decisions across DoorDash's operations, logistics, and business teams using SQL, Python, and visualization tools.
Designs and maintains large-scale data pipelines and warehouses for DoorDash’s logistics platform in São Paulo, using Python, SQL, Spark, and cloud tools like AWS/GCP.
Builds and scales data pipelines, warehouses, and analytics systems for DoorDash’s logistics platform in São Paulo, using Python, SQL, Spark, and cloud tools.
Build and maintain data pipelines, metrics, and dashboards to enable data-driven decisions across DoorDash’s operations using SQL, Python, and tools like Tableau and Spark.
About the Team DoorDash is a data driven organization and relies on timely, accurate and reliable data to drive many business and product decisions. Data is at the foundation of DoorDash success. The Data Engineering…
About the Team This position is dedicated to professionals with disabilities (PCD), in accordance with Brazilian Law No. 8.213/91 (Lei de Cotas). At DoorDash, we believe diverse teams build better products. We are…
Senior Backend Python engineer designing and evolving corporate AI assistants (ATS, internal platforms) using LangGraph, LangChain, microservices, and distributed systems in a fully remote role.
Data Engineer building and maintaining ETL pipelines, data models, and a lakehouse infrastructure using Azure Synapse Analytics, Databricks, Python, and PySpark in a hybrid role in Kuala Lumpur.
Data Engineer building and maintaining data infrastructure, pipelines, and storage solutions (data lakes/warehouses) using Python, PySpark, SQL, and Power BI to power analytics and BI for a vacuum valve manufacturer.
The Data Engineer will design and implement robust data pipelines using Azure cloud services, Python, and PySpark to ensure seamless data flow and high-quality analytics. The role involves collaborating with stakeholders to optimize data ingestion and transformation processes across various enterprise systems.
Lead Data Engineer & BI Architect on an insurance-sector project, working with Azure and Databricks to migrate data models to Data Lake, integrate corporate applications, and deliver Power BI dashboards.
Build and maintain specification-driven web data extraction pipelines using Python, Scrapy, Playwright, and LLM-augmented approaches (LangChain, autonomous agents, MCP servers) to create a self-healing, component-based extraction platform.
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