Senior Data Engineer
Design and optimize complex SQL Server solutions with a focus on performance tuning and data modeling. Automate processes using PowerShell and integrate systems via APIs and LLM-driven workflows.
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Design and optimize complex SQL Server solutions with a focus on performance tuning and data modeling. Automate processes using PowerShell and integrate systems via APIs and LLM-driven workflows.
Lead a high-performing data engineering team to build scalable, event-driven data infrastructure and pipelines. Design data models and architectures that support analytics, operational systems, and AI-enabled applications.
The role involves processing, refining, and analyzing data using ETL/ELT processes and integrations on cloud-based platforms. You will collaborate with clients, analysts, and other developers to ensure documented and managed development within client environments.
Lead and mentor multiple data engineering teams in the design, build, and maintenance of high-quality data products using Databricks. Establish engineering standards, optimize Spark performance, and oversee the migration from legacy analytical platforms to a modern streaming architecture.
Design, build, and maintain scalable production-grade data systems and resilient pipelines to support analytics and machine learning. Collaborate with cross-functional teams to translate business needs into technical solutions while mentoring other engineers.
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Develop data architectures, pipelines, and integration solutions to ensure data quality and availability. Consult clients on implementing modern data platforms and create foundations for data-driven decision-making.
Design and maintain scalable ELT pipelines and production-grade data models within a Snowflake-based ecosystem. Collaborate with cross-functional teams to translate business requirements into high-performance data solutions for analytics and ML.
Develop and maintain ETL processes using Python and PySpark within Azure Synapse Analytics to ensure efficient data extraction and loading. Design and optimize data warehousing structures, including star schemas and data lakes, to enhance scalability and performance.
Design, build, and operate scalable data pipelines and infrastructure to ensure high-quality data for analytics and data science. This includes implementing MLOps automation and optimizing workflows for performance and cost.
Design, build, and operate scalable data pipelines and infrastructure to ensure high-quality data is available for analytics and data science. This includes implementing MLOps automation and optimizing workflows for performance and cost.
The role involves performing structural engineering tasks specifically for data center projects. Responsibilities include designing and analyzing structures to support critical infrastructure.
Develop and maintain robust data pipelines and analytical data models using SSIS, SSAS, and SQL Server. Build reporting solutions with Power BI and SSRS while collaborating with business teams to translate requirements into technical solutions.
Provide engineering support to customers in the data center market for the selection and application of industrial products. Collaborate with MEP contractors and internal teams to ensure system requirements are met and research emerging technology trends.
Own the organization-wide data architecture, defining standards and patterns for IoT ingestion, storage, and processing infrastructure. Provide design oversight to engineering teams and partner with leadership to drive strategic data initiatives and AI/ML infrastructure.
Manage the lifecycle and firmware updates of server hardware while troubleshooting infrastructure and connectivity issues. Collaborate with cross-functional teams to standardize hardware configurations and develop operational procedures.
The Data Engineer will design and optimize enterprise data models using dimensional modeling to support business processes. They will collaborate with the engineering team and stakeholders to build high-performance, low-cost database architectures.
You will design, build, and optimize scalable data pipelines and architectures to support data-driven decision-making across various business domains. Additionally, you will collaborate with cross-functional teams to translate business requirements into reliable, high-performance technical solutions.
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You will design and implement scalable data warehouse solutions while collaborating with an international team to drive data-driven insights. Additionally, you will lead code reviews, suggest process improvements, and manage the full development lifecycle of data pipelines.
The Senior Staff Data Engineer designs and implements complex data integration pipelines and scalable data infrastructure to support AI, BI, and analytical systems. This role also involves mentoring junior engineers, establishing technical standards, and collaborating with cross-functional teams to deliver optimized data solutions.
The Forward Deployed Engineer will partner with business stakeholders to rapidly build and deploy automation and AI-driven solutions. This role involves full-stack engineering, including data pipelining, backend development, and the creation of dashboards to solve complex business problems.
Design, build, and maintain scalable data pipelines and infrastructure using Google Cloud Platform services. Collaborate with data scientists and analysts to ensure data accuracy, performance, and availability for business insights.
The Team Lead manages a team of engineers and technicians to ensure the accurate and timely completion of structural engineering scopes for data center projects. They are responsible for overseeing project planning, design package production, and providing mentorship to junior staff.
You will transform raw engineering data into structured, high-fidelity datasets to train and evaluate AI systems for design and manufacturing. This involves building mechanical components in CAD, creating labeling workflows, and collaborating with research teams to define data quality standards.
Design and operate large-scale, automated intelligence collection systems to crawl and index data from surface, deep, and dark web sources. Build and maintain robust ETL pipelines to normalize, enrich, and integrate threat intelligence into AI-driven cybersecurity platforms.
Build and maintain resilient streaming and batch data pipelines to ingest, normalize, and distribute market and trading data. Develop self-serve tooling and data governance frameworks to ensure high-quality, observable, and performant data products across the organization.
Design and develop data pipelines and processing solutions using Azure Databricks and Python. Collaborate with business stakeholders to gather requirements and manage data products while ensuring data quality and security.
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You will design, build, and maintain scalable data pipelines and infrastructure using AWS, Python, and Databricks. Additionally, you will collaborate with cross-functional teams to deliver data products and provide technical mentorship to junior engineers.
You will define the architecture for the data platform and lead the design of scalable, low-latency pipelines for high-volume payment transactions. Additionally, you will mentor senior engineers and partner with cross-functional teams to ensure data reliability and business value.
Lead the development and continuous improvement of mechanical and plumbing engineering standards for large-scale data center projects. Oversee technical reviews, drive innovation, and mentor a team of engineers to ensure consistent, high-quality project delivery.
The Senior Electrical Engineer will provide subject matter expertise on electrical design, construction permitting, and project engineering for data center infrastructure. This role also involves leading and mentoring a team of engineers to ensure design quality, efficiency, and adherence to industry standards.
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