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ETL Data Engineer
Charlotte, NC - Onsite
6 Months
Job Description
ETL Data Engineer
Charlotte, NC - Onsite
6 Months
Job Description
- 5-8 years of overall work experience in relevant fields, demonstrating a solid background in data engineering.
- The work model is hybrid, allowing for a combination of in-office and remote work to accommodate team collaboration and productivity.
- Expert knowledge of retail and eCommerce, showcasing the ability to address specific industry challenges.
- Strong working knowledge of ETL processes, enabling effective data management and transformation.
- Design and develop end-to-end ETL / ELT pipelines for ingesting, transforming, and loading data from multiple sources
- Build and maintain cloud-based data pipelines on Azure, including orchestration, automation, and monitoring
- Design and implement data warehouse solutions, including data modeling for analytical use cases
- Apply strong SQL skills for data transformation, validation, and analytical processing
- Support downstream analytics and reporting platforms, including Power BI
- Exposure to modern data processing concepts and AI-assisted tools to enhance pipeline development and data workflows
- Demonstrated expertise in ETL tools and methodologies, ensuring efficient data workflow
- Implement data ingestion pipelines from diverse sources, ensuring large-scale structured and unstructured data transmission between systems.
- Develop data aggregation pipelines that effectively feed analytic and reporting solutions.
- Maintain scalable code that adheres to company standards and is thoroughly documented.
- Participate actively in agile SCRUM ceremonies, including refinement, planning, stand-ups, and retrospectives.
- Flushing out business requirements and adding acceptance criteria to user stories.
- Engage in peer review code sessions to uphold code quality.
- Communicate effectively with management regarding proposed solutions and challenges.
- Supervise and resolve data issues, demonstrating creative problem-solving skills.
- Maintain in-depth knowledge of the data ecosystem and trends, acting as a domain expert.
- Recommend new tools to enhance the current stack and efficiently address data needs.