About the role
Tiger Analytics is a global AI and analytics consulting firm. With data and technology at the core of our
solutions, our 2800+ tribe is solving problems that eventually impact the lives of millions globally. Our culture
is modeled around expertise and respect with a team first mindset. Headquartered in Silicon Valley, you’ll find
our delivery centers across the globe and offices in multiple cities across India, the US, UK, Canada, and
Singapore, including a substantial remote global workforce.
We’re Great Place to Work-Certified™. Working at Tiger Analytics, you’ll be at the heart of an AI revolution.
You’ll work with teams that push the boundaries of what is possible and build solutions that energize and
inspire.
About the role:
- Experience in data profiling, data analysis, or data quality roles
- Comfort with SQL — ability to write and validate queries independently
- Familiarity with Python or any scripting language for test automation
- Strong attention to detail and structured thinking
- Ability to read and interpret data in business context — not just technical context
- Good communication skills — able to translate data findings into clear, non-technical language
- Experience with JIRA or similar tools for task and defect tracking
- Exposure to AI or LLM-based applications
Experience with ontology, knowledge graphs, or semantic data concepts
- Familiarity with AWS services — Redshift, S3, SageMaker
- Background in pharmaceutical or enterprise IT data domains
Required Qualifications
- Experience in data profiling, data analysis, or data quality roles
- Comfort with SQL — ability to write and validate queries independently
- Familiarity with Python or any scripting language for test automation
- Strong attention to detail and structured thinking
- Ability to read and interpret data in business context — not just technical context
- Good communication skills — able to translate data findings into clear, non-technical language
- Experience with JIRA or similar tools for task and defect tracking
- Exposure to AI or LLM-based applications
Experience with ontology, knowledge graphs, or semantic data concepts
- Familiarity with AWS services — Redshift, S3, SageMaker
- Background in pharmaceutical or enterprise IT data domains
