Tiger Analytics is a fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.
We are seeking a skilled Data Engineer to join our team. The ideal candidate will have a strong background in data engineering, cloud-based solutions, and a proven track record of building and managing scalable data pipelines on AWS. The Data Engineer will work closely with cross-functional teams to develop, maintain, and optimize data solutions that support critical business insights. We are looking for someone who can bring their vision to the table and implement positive change in taking the company's data analytics to the next level.
- 3-5 years of experience in data engineering with a focus on AWS cloud solutions.
- 3+ years of experience in Designing, developing, and maintaining scalable and secure ETL/ELT pipelines using AWS services.
- Creating and optimizing complex data processing and data transformation pipelines using python
- Hands-on experience with AWS services like Glue, Lambda, S3, Redshift, and Athena.
- Strong knowledge of SQL for querying and managing relational databases.
- Experience with big data tools such as Apache Spark, Hadoop, or EMR.
- Implement best practices for cloud-based data architecture and pipeline management.
- Understanding of data modeling concepts and best practices.
- Familiarity with CI/CD pipelines and version control tools like Git.
- AWS certifications (e.g., AWS Certified Data Analytics, AWS Certified Solutions Architect).
This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.
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