Tech Architect - Data

Location: IN MH Mumbai Eureka

Time Type: Full time

Job Description

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth.


If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi!

You will be working as a Data architect within the domain, designing and delivering big data pipelines for structured and unstructured data that are running across multiple geographies, helping healthcare organizations achieve their business goals with use of data ingestion technologies, cloud services & DevOps. You will be working with Architects from other specialties such as Cloud engineering, Software engineering, ML engineering to create platforms, solutions and applications that cater to latest trends in the healthcare industry such as digital diagnosis, software as a medical product, AI marketplace, amongst others.
Role & Responsibilities:
Work with cloud engineers and customers to solve big data problems by developing utilities for migration, storage and processing on Google Cloud.
Design and build a cloud migration strategy for cloud and on-premise applications.
Diagnose and troubleshoot complex distributed systems problems and develop solutions with a significant impact at massive scale.
Build tools to ingest and jobs to process several terabytes or petabytes per day.
Design and develop next-gen storage and compute solutions for several large customers.
Be involved in proposals, RFPs and provide effort estimates, solution design etc.
Communicate with a wide set of teams, including Infrastructure, Network, Engineering, DevOps, SiteOps teams, and cloud customers.
Build advanced tooling for automation, testing, monitoring, administration, and data operations across multiple cloud clusters.
Better understanding of Data modeling and governance