Highly Skilled AWS Data Engineer
4 days ago
Lion is a leading company in the industry, offering 'growth on tap' and endless opportunities for career advancement. With a focus on innovation and data-driven decision making, we are seeking a highly skilled Senior AWS Data Engineer to join our team.
As a key member of our Data & Analytics platform, you will be responsible for designing, building, testing, and deploying optimized, highly available, and reliable data pipelines and architectures using relevant tools. Your expertise will not only enhance current capabilities but also foster a culture of data-driven innovation, aligned closely with Lion's rigorous data governance practices.
We are committed to diversity, equity, and inclusion, and leveraging unique perspectives to innovate and grow. Our ideal candidate has extensive experience with AWS architecture, technologies, and services, as well as strong understanding of Data & Analytics concepts and technologies.
The estimated salary for this position is $120,000 - $180,000 per year, depending on location and qualifications. If you're looking for a challenging and rewarding role that offers growth opportunities and a competitive salary, we encourage you to apply.
Key Responsibilities:
- Design, build, test, and deploy optimized data pipelines and architectures
- Drive business value creation by integrating new data platform toolsets into an innovation pipeline
- Assemble large, complex structured and unstructured data sets that meet business requirements
- Update existing data models and metadata repositories for new use cases
- Identify, design, and implement internal process improvements
Requirements:
- Minimum 8 years of experience in Modern Data Platforms (AWS, Azure, etc.) and Data Engineering
- Strong Agile delivery skills and a degree in Computer Science, Data Science, IT, or a related field
- Proficiency in data engineering tools and languages such as SQL, Python, Athena, Redshift, and Glue
- Deep knowledge of Data Architecture, Data Modeling, Data Marts, and Metadata Management best practices
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