We are looking for a Data Engineer with experience in the Azure ecosystem to design, build, and optimize modern data solutions. This role will be key in building robust pipelines, scalable architectures, and data platforms oriented toward advanced analytics and strategic decision-making. You will work in dynamic environments under Agile methodologies, collaborating with engineering, analytics, and business teams to ensure data availability, quality, and efficiency. Responsibilities - Design, develop, and maintain scalable and efficient data pipelines (ETL/ELT). - Build and optimize modern data architectures (Data Warehouse and Lakehouse). - Implement data models (primarily dimensional modeling using the Kimball approach). - Integrate multiple data sources ensuring quality, consistency, and availability. - Perform data profiling and anomaly detection. - Optimize SQL queries and performance across data platforms. - Collaborate on defining standards, best practices, and data architecture. - Implement CI/CD processes and DevOps practices applied to data pipelines. - Work under Agile methodologies (Scrum/Kanban) in collaboration with multidisciplinary teams.

We are looking for a Data Engineer with experience in the Azure ecosystem to design, build, and optimize modern data solutions. This role will be key in building robust pipelines, scalable architectures, and data platforms oriented toward advanced analytics and strategic decision-making. You will work in dynamic environments under Agile methodologies, collaborating with engineering, analytics, and business teams to ensure data availability, quality, and efficiency. Responsibilities - Design, develop, and maintain scalable and efficient data pipelines (ETL/ELT). - Build and optimize modern data architectures (Data Warehouse and Lakehouse). - Implement data models (primarily dimensional modeling using the Kimball approach). - Integrate multiple data sources ensuring quality, consistency, and availability. - Perform data profiling and anomaly detection. - Optimize SQL queries and performance across data platforms. - Collaborate on defining standards, best practices, and data architecture. - Implement CI/CD processes and DevOps practices applied to data pipelines. - Work under Agile methodologies (Scrum/Kanban) in collaboration with multidisciplinary teams.

Hello and thank you for your interest! We're looking for folks nationwide who are great at data entry and typing. We offer a flexible work from home remote position that allows you to stay home with the family! The pay range is flexible from $16/ph to $30/ph DOE and level of experience. You'll meet these requirements to work from home remotely • Stable Internet connection • Work can be done using the following: Phone device, laptap or computer • Must be able to type accurately with a minimum speed of 30 words per minute • Able to focus on tasks without being distracted • Must be resident of the US • Not afraid of emailing clients as needed We're looking for folks who we can depend on who can work from home remotely without distraction and are go-getters. Pay range from 16 to 30 hourly depending on the role, level of experience and proven ability to work from home at the same level as from an office. Data entry clerks come from all different backgrounds including, data entry, telemarketing, customer service, sales, clerical, secretary, administrative assistant, warehouse, inventory, receptionist, call center, part-time, retail fields & more • Must be 16 year of age or older • Must be proficient with basic PC skills • Must have an internet connection • Basic english written language • Basic english spoken language Thank you for your interest!

• Develop and improve services to load, transform and consume data, using cutting-edge technologies and the best tools available in the market; • Collaborate with data science and operations PMs to maintain a deep understanding of their business needs and support projects that rely on data infrastructure; • Continuously pursue improvements in scalability, resource efficiency, latency, and flexibility for our data services;