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Execute end-to-end data engineering work: ELT, processing structured and unstructured data, build scalable automation, develop data solutions, collaborate with data science and product teams, and communicate with clients.

Lead and manage end-to-end data engineering projects: design and build data platforms, ETL/data pipelines, data lakes, streaming hubs, and ML training/scoring services. Collect requirements, ensure quality, troubleshoot, mentor team members, deliver technical training, and communicate with clients and stakeholders. Collaborate with consultants and data scientists in an agile environment.

Build, monitor, and troubleshoot data pipelines and storage on Azure (Data Factory, Data Lake). Support data scientists, implement ELT and data governance, ensure data quality, and document workflows while collaborating with stakeholders.

Translate business problems into analytical approaches; analyze structured and unstructured data; build and maintain ETL/ELT pipelines and scalable data-processing solutions; perform data-quality checks and optimization; develop automation and analytical solutions using SQL, Python or Scala; support reporting, advanced analytics and ML use cases; collaborate with cross-functional teams and communicate findings to technical and non-technical stakeholders while managing multiple client deliverables.

Design and build production data platforms and ETL/ELT pipelines using Azure and open-source tools. Collaborate with data scientists and stakeholders to deliver data lakes, streaming hubs, and analytics solutions. Collect requirements, mentor teammates, provide technical training, and support big-data strategies across digital marketing, e-commerce and BI use cases.

Lead eCommerce and AI initiatives to improve customer journeys and frontend experiences. Translate business needs into technical solutions, drive chatbot and conversational commerce projects, evaluate AI opportunities, collaborate with architects and product teams, and manage small-to-medium IT projects from concept to rollout.

Lead client engagements, translate business problems into analytics and ML solutions, provide project oversight, develop presentations, identify new opportunities, and mentor junior team members while orchestrating the team.

The Senior DevOps Engineer will design and maintain integration solutions in a multi-cloud environment, focusing on automation and system performance, while collaborating with developers and architects.

Design, build and maintain end-to-end data solutions including ETL, data processing, automation and scalable pipelines. Work with data scientists and cross-functional teams to acquire, clean, integrate and analyze structured and unstructured data. Diagnose issues, develop solutions, and communicate findings to clients and stakeholders.

Lead data engineering efforts: design architecture, build and deploy ETL/ELT pipelines, manage Azure-based data platforms, collaborate with data scientists, coach team members, and engage stakeholders to deliver data products and analytics.