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Build and maintain source adapters and normalization logic to transform raw data from disparate systems into a consistent risk-signal schema. Implement robust ETL/ELT pipelines with a focus on observability, data quality, and near-real-time event streaming.
You will transform complex data into actionable insights to support revenue growth, operational efficiency, and strategic planning. This involves building predictive models, designing interactive dashboards, and presenting findings to senior leadership.
The Data Engineer will design and maintain optimal data pipeline architectures while extending the company's machine learning platform. They are also responsible for supervising junior engineers and building analytics tools to support business performance metrics.
The Data Engineer will design, build, and maintain ETL/ELT pipelines while ensuring data quality and reliability across the platform. They will collaborate with AI and product teams to support analytics, reporting, and data modeling initiatives.
The Data Engineer will design, build, and maintain scalable data pipelines and cloud-based data platforms using Microsoft Azure and Microsoft Fabric. They will also support the modernization of existing workloads and ensure high-quality data availability for analytics and reporting teams.
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The role involves analyzing and implementing architecture and configuration changes to support tool enhancements, automation, and system integration. You will also perform technical research, troubleshoot environment issues, and develop frontend components while ensuring seamless data flow.
You will design, develop, and maintain ETL/ELT processes for data migration between CRM systems in a production environment. Additionally, you will monitor database performance, optimize SQL queries, and support implementation projects for end clients.
You will develop and maintain data processing pipelines, datamarts, and cloud-based solutions using AWS technology. Additionally, you will support data consumers with query optimization and ensure the reliability of data assets across the organization.
The Data Engineer II designs, builds, and maintains reliable data pipelines and API integrations to support analytics and operational reporting. This role involves collaborating with senior engineers to deliver scalable solutions while contributing to platform modernization and data quality initiatives.
The Data Engineer will build, maintain, and optimize data pipelines to ingest information into Snowflake while developing scalable data models using dbt. They will also partner with cross-functional business teams to translate data needs into practical solutions and support analytics and machine learning initiatives.
You will design, develop, and maintain data-intensive applications and ETL/ELT pipelines using cloud technologies like Snowflake, Spark, and Azure. Additionally, you will collaborate with cross-functional teams to deliver scalable data solutions and AI-powered features within an agile environment.
The Data Engineer will design, build, and maintain scalable cloud-native data pipelines and infrastructure to support analytics and real-time processing. They will collaborate with cross-functional teams to ensure data accessibility, reliability, and security across enterprise platforms.
The role involves designing, developing, and maintaining robust data infrastructure and pipelines to ensure efficient data movement and transformation. You will collaborate with cross-functional teams to implement data models, ensure data quality, and support business intelligence needs.
You will architect and manage robust data pipelines that bridge on-premise SQL Server environments with Google Cloud Platform. Additionally, you will modernize data ingestion processes and optimize BigQuery architectures to ensure high-speed, cost-effective data performance.
You will be responsible for building and maintaining scalable data integration mechanisms and processing pipelines using SQL, Python, and Apache Spark. Additionally, you will contribute to architectural decisions, develop CI/CD pipelines, and ensure high data quality and reliability across the centralized platform.
Design, build, and maintain robust data pipelines and engineering workflows using SQL, Python, and Databricks. Support critical initiatives including data ingestion, process automation, transformation, and data quality assurance.
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Build and maintain robust data pipelines while optimizing the data platform for scalability and performance. Collaborate with cross-functional teams to address data needs and monitor model performance and accuracy.
Design, develop, and maintain scalable data engineering solutions using Azure and Snowflake platforms. Build and optimize ETL/ELT pipelines to ingest, transform, and load data from various sources while ensuring data quality and security.
You will design, build, and maintain scalable data pipelines and services using Python, SQL, and cloud technologies. Additionally, you will focus on continuous improvement by refactoring existing systems, implementing data quality checks, and optimizing performance.
Design, build, and maintain scalable data pipelines while ensuring data quality and reliability across heterogeneous systems. Collaborate with product and engineering teams to translate business requirements into effective data solutions and mentor junior team members.
Design, build, and maintain scalable data pipelines and infrastructure for batch and real-time data processing. Collaborate with cross-functional teams to ensure high-quality, reliable, and accessible data for analytics and machine learning applications.
The Data Engineer will lead the design, development, and optimization of enterprise data solutions, including building robust data pipelines and integrating diverse data sources. They will also oversee the architecture and administration of Power BI to enable advanced analytics and reporting across the organization.
You will be responsible for developing and maintaining the corporate data warehouse and building robust EL/ELT/ETL pipelines. Additionally, you will manage data synchronization, ensure data quality, and optimize costs across cloud-based data systems.
You will develop and maintain corporate data warehouses and build robust ELT/ETL pipelines to support business users and ML engineers. Additionally, you will focus on data quality, governance, and cost optimization across cloud-based data systems.
The Data Engineer will develop and maintain the corporate data warehouse using cloud technologies and best practices. They will also build EL/ELT/ETL pipelines and ensure data quality and governance across internal and external systems.
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Develop and maintain corporate data warehouses and ELT/ETL pipelines to support business users, analysts, and ML engineers. Ensure data quality and governance while optimizing costs and managing data synchronization across systems.
The Data Engineer will develop and maintain the corporate data warehouse using cloud technologies and best practices. They will also build EL/ELT/ETL pipelines and ensure data quality and governance across internal and external systems.
You will design, build, and maintain scalable data architectures and mission-critical data pipelines to support event-driven analytics and machine learning. Additionally, you will collaborate with cross-functional teams, mentor junior engineers, and ensure the performance and reliability of data processing workflows.
The Data Engineer will design, develop, and maintain scalable ETL pipelines and data storage solutions to support client data needs. They will collaborate with cross-functional teams to ensure high-quality data delivery while adhering to Agile development practices.
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