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The Data Engineer will design and build scalable data lakehouse platforms and ETL pipelines on AWS for a government project. The role involves implementing data quality frameworks, using infrastructure-as-code tools, and ensuring robust data governance.
The Data Engineer will design, build, and maintain scalable data pipelines and architecture for Finance stakeholders using Databricks and Google Cloud Platform. The role focuses on ingesting, processing, and transforming large-scale datasets to support analytical and operational requirements.
The Databricks Solution Architect will design and implement scalable, cloud-native big data platforms and lakehouse architectures for clients. This role involves leading data modernization initiatives, collaborating with stakeholders, and providing technical leadership in data engineering and AI integration.
The Databricks Data Engineer will design and implement scalable ETL/ELT pipelines and Lakehouse architectures to support advanced analytics and AI use cases for clients. This role requires deep expertise in the Databricks ecosystem, including Spark, Delta Lake, and Unity Catalog, to build robust, secure, and governed data solutions.
The Snowflake Data Engineer will design, build, and maintain secure, high-performing data pipelines and architectures for clients using Snowflake and cloud-native platforms. This role involves collaborating with cross-functional teams to deliver scalable data solutions and advanced analytics capabilities.
Design and implement Snowflake-based cloud data platforms for enterprises, enabling scalable, secure data solutions and AI-driven insights while guiding clients through data modernization.
The Databricks Solution Architect designs and delivers scalable, cloud-native big data platforms and lakehouse architectures for enterprise clients. This role involves strategic consulting, leading data modernization initiatives, and integrating AI/ML capabilities using technologies like Databricks, Spark, and Kafka.
The Databricks Data Engineer will design and implement scalable data pipelines and Lakehouse architectures to support advanced analytics and AI use cases for clients. This role involves working with the Databricks platform, cloud-native environments, and ETL/ELT workflows to deliver robust, secure data solutions.
The Snowflake Data Engineer will design, build, and maintain secure, high-performing data pipelines and ecosystems for clients. The role involves collaborating with cross-functional teams to implement ETL/ELT processes and advanced analytics solutions using Snowflake and cloud-native technologies.
Design and implement Snowflake-based cloud data platforms for enterprise clients, guiding data modernization and enabling advanced analytics using Snowflake, SQL, ETL/ELT, and cloud ecosystems.
The Lead Data Engineer will shape the technical direction of a Microsoft Fabric environment and manage data pipelines from ERP, CRM, and digital sources. The role involves mentoring engineers and improving data engineering standards within a cloud-based Azure platform.
The Data Engineer will design, develop, and maintain data pipelines using Databricks, Python, and SQL within a Microsoft Azure environment. This hybrid role involves optimizing ETL/ELT processes and collaborating with stakeholders to enhance the company's reporting and analytics platform.
This role involves automating software delivery, infrastructure provisioning, and security controls for the Case Management Modernization program using AWS, CI/CD pipelines, and Infrastructure as Code. The engineer will integrate security into the full lifecycle while optimizing cloud data platform performance and reliability.
The Data Engineer will design and maintain scalable ETL/ELT pipelines using Databricks, Python, Spark, and SQL to support analytics and AI/ML workloads. The role also involves modernizing existing Microsoft-based data environments, including SQL Server, SSIS, and SSRS.
Data Engineer designing and maintaining ETL/ELT pipelines in Databricks (Python, Spark, SQL) to power reporting, analytics, and AI/ML workloads while modernizing legacy SQL Server/SSIS/SSRS infrastructure.
Pre-sales Senior Solutions Architect at Dell Brazil helping enterprise customers design and adopt modern data, analytics, and AI solutions—including data warehouses, lakehouses, GenAI, and RAG—through discovery, architecture, demos, and POCs.
Lead Software Engineer building a Data & AI Platform for JPMorgan Chase's Payments Technology team—designing scalable data pipelines with Spark, Airflow, Kafka, Flink, and Databricks, and leading an Agentic AI initiative for automated lakehouse operations.
Designs and maintains large-scale data pipelines and warehouses using Ab Initio and Snowflake, focusing on ETL/ELT, healthcare data integration, and cloud modernization in an Azure environment.
Principal Data Engineer building cloud-based data and reporting platforms using big data technologies (Hadoop, HBase, MongoDB, Cassandra), coding in Java/Scala/Python, automating CI/CD pipelines, and leading enterprise-level data architecture for analytics at a financial services firm.
Build and maintain Allstate’s Microsoft Fabric data platform, designing Bronze-to-Gold pipelines, dimensional models, and Power BI semantic layers to power insurance analytics, Copilot-ready reporting, and regulatory compliance.
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