Tiger Analytics is pioneering what AI and analytics can do to solve some of the toughest problems faced by organizations globally. We develop bespoke solutions powered by data and technology for several Fortune 100 companies. We have offices in multiple cities across the US, UK, Canada, India, and Singapore, and a substantial remote global workforce.
If you are passionate about working on business problems that can be solved using structured and unstructured data on a large scale, Tiger Analytics would like to talk to you. We are seeking an experienced and dynamic Data Engineer to play a key role in designing and implementing robust data solutions that help in solving the client's complex business problem
Requirements
Responsibilities:
- Design, develop, and maintain scalable data pipelines using Scala, DBT, and SQL.
- Implement and optimize distributed data processing solutions using MPP databases and technologies.
- Build and deploy machine learning models using distributed processing frameworks such as Spark, Glue, and Iceberg.
- Collaborate with data scientists and analysts to operationalize ML models and integrate them into production systems.
- Ensure data quality, reliability, and integrity throughout the data lifecycle.
- Continuously optimize and improve data processing and ML workflows for performance and scalability.
Requirements:
- 5+ years of experience in data engineering and machine learning.
- Proficiency in Scala programming language for building data pipelines and ML models.
- Hands-on experience with DBT (Data Build Tool) for data transformation and modeling.
- Strong SQL skills for data querying and manipulation.
- Experience with MPP (Massively Parallel Processing) databases and distributed processing technologies.
- Familiarity with distributed processing frameworks such as Spark, Glue, and Iceberg.
- Ability to work independently and collaboratively in a team environment.
Benefits
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.
