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Tiger Analytics is seeking a data engineer to design and implement scalable data pipelines and data lakehouse architectures on Azure Databricks. You will work on complex data workflows, apply PySpark and Python to build analytics products, and ensure strong instrumentation and CI/CD practices.
The role requires collaboration with cross-functional teams and a focus on delivering measurable business outcomes.
Tiger Analytics is a global leader in AI and analytics, helping Fortune 1000 companies solve their toughest challenges. We offer fullstack
AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to
push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our purpose
is to provide certainty to shape a better tomorrow.
Our team of 6000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore and Australia, working closely
with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. Many of our team leaders rank in Top
10 and 40 Under 40 lists, exemplifying our dedication to innovation and excellence.
We are a Great Place to Work-Certified (2022-24), recognized by analyst firms such as Forrester, Gartner, HFS, Everest, ISG and
others. We have been ranked among the Best’ and ‘Fastest Growing’ analytics firms lists by Inc., Financial Times, Economic Times
and Analytics India Magazine.
Curious about the role? What your typical day would look like?
We are seeking street-smart and technically strong Data Engineers who can take ownership of designing and developing cutting-edge
data and AI platforms using Azure-native technologies and Databricks. You will play a critical role in building scalable data pipelines,
modern data architectures, and intelligent analytics solutions.
Bachelor’s degree (B.E/B.Tech) in Computer Science, Information Technology, or a related field from a reputed institute
(preferred).