Senior Data Engineer
Design, develop, and deploy bots using Automation Anywhere A360 and Excel VBA macros. Collaborate with stakeholders to identify automation opportunities and maintain documentation such as PDDs and SDDs.
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Design, develop, and deploy bots using Automation Anywhere A360 and Excel VBA macros. Collaborate with stakeholders to identify automation opportunities and maintain documentation such as PDDs and SDDs.
Construct and maintain scalable data pipelines and workflows across Salesforce, Oracle ERP, and Azure Cloud. Collaborate with cross-functional teams to ensure data quality and support analytics and reporting needs for RevOps and GTM systems.
The role involves designing, implementing, and scaling data processing pipelines for global road networks. You will also monitor performance metrics and implement security best practices for high-definition maps.
Develop modern analytics and AI solutions using the Microsoft ecosystem, from data foundations to productive business use. Design scalable data platforms and implement Generative AI scenarios such as LLMs and RAG to support business decision-making.
Architect and build the foundational data lakehouse and pipelines to transform raw financial data into trustworthy, intelligence-ready datasets. Establish data quality, observability, and security standards within a regulated environment to enable AI/ML and analytics.
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Lead the design and implementation of a modern AWS and Databricks Lakehouse platform to drive enterprise analytics strategy. Manage the full ETL/ELT lifecycle while mentoring a small team and ensuring data reliability and governance.
Build and maintain reliable, scalable big data pipelines and commercial products end-to-end. Collaborate with product managers to define requirements and mentor junior engineers through code reviews and technical guidance.
Design and maintain backend services, REST APIs, and big data pipelines to power customer-facing insights and analytics. Develop a query engine and scale data processing pipelines to handle large volumes of activity data for the Unified Data Platform.
Design and maintain scalable batch and real-time data pipelines on GCP using Medallion Architecture. Develop high-performance data transformations and optimize complex SQL queries for large-scale analytical workloads.
Design and implement complex data solutions, architectures, and scalable pipelines for customers. Translate business requirements into technical tasks to help organizations capitalize on data and AI opportunities.
Design and manage the end-to-end data platform architecture, from integration and transformation to data delivery. Lead the development of robust data pipelines and establish technical standards for data quality and modeling within Databricks.
Design and own the end-to-end data platform architecture, including ingestion, transformation, and serving layers. Lead the development of robust data pipelines and enforce data quality standards to power business-critical decisions.
Design, develop, and optimize scalable data pipelines and solutions primarily using Snowflake. Collaborate with business teams to translate requirements into robust technical solutions and ensure data reliability and traceability.
Design and implement electrical systems for hyperscale and colocation data centers, including power distribution and backup systems. Develop electrical schematics, calculations, and drawings while ensuring compliance with industry standards and codes.
Design and implement electrical systems for hyperscale and colocation data centers, including power distribution and backup systems. Develop electrical schematics, calculations, and drawings while ensuring compliance with industry standards and codes.
Design and implement electrical systems for hyperscale and colocation data centers, including power distribution and backup systems. Develop electrical schematics, calculations, and drawings while ensuring compliance with industry standards and codes.
Build and maintain data ingestion pipelines from APIs and other sources using Python and SQL. Support marketing data modeling and collaborate with analytics teams to deliver campaign performance datasets.
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Design, develop, and optimize AI/ML models and pipelines to power cybersecurity behavioral detectors. Collaborate with cross-functional teams to integrate these features into a scalable, fault-resilient platform.
Design, build, and maintain robust ETL/ELT data pipelines and infrastructure on Google Cloud Platform to power company analytics. Collaborate with stakeholders to deliver reliable data models and manage workflow orchestration using Apache Airflow.
Design, build, and maintain robust ETL/ELT data pipelines and infrastructure on Google Cloud Platform to power company analytics. Collaborate with stakeholders to deliver reliable data models and manage workflow orchestration using Apache Airflow.
Design and build a greenfield analytical data platform on GCP to power internal and customer-facing AI agents. This includes constructing ELT/CDC pipelines, managing orchestration, and developing the retrieval layer for RAG systems.
Build and maintain secure, scalable data systems and pipelines that enable AI applications to access trusted internal data. Partner with analytics, marketing, and product teams to define infrastructure and governance standards for AI-driven experiences.
Drive the architecture and execution of high-impact engineering initiatives to deploy AI/ML models for network traffic analysis. Lead cross-functional technical initiatives and provide mentorship to software engineers to foster engineering excellence.
The Data Engineer II is responsible for driving data transformation projects, including managing ingestion pipelines and optimizing the Snowflake data platform. They will ensure seamless data flow across the enterprise while supporting data governance and financial regulatory compliance.
Design and maintain a cloud-native data lakehouse using Medallion architecture to deliver trusted data from ingestion to analytics. Implement data quality observability, automated validation, and scalable ETL/ELT pipelines within the Azure ecosystem.
Architect and maintain large-scale Spark-driven data pipelines and backend ingestion workflows to support advanced analytics. Develop AI-augmented tooling, including MCP servers and AI agents, to automate and accelerate data engineering lifecycles.
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Design, develop, and deploy Power BI solutions and data models to provide advanced analytics and business insights. Manage data ingestion, ETL processes, and performance tuning for complex SQL and DAX queries within a TAX platform.
Design and develop high-performance data pipelines and real-time processing solutions using Python and Go. Manage infrastructure as code with Terraform and ensure system reliability through monitoring and testing strategies.
Design and deliver end-to-end data platforms and scalable ETL/ELT pipelines for analytics, BI, and AI-ready products. Collaborate with stakeholders to implement lakehouse architectures while mentoring engineers and ensuring data quality and security standards.
Design and optimize heat rejection and HVAC systems specifically for data centers, ensuring redundancy and energy efficiency. Conduct CFD analysis and heat load calculations to maintain optimal cooling and airflow for critical IT equipment.
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