Senior Consultant – DATA ENGINEER
Company Name:-
AstraZeneca
Job Location:-
Chennai, Tamil Nadu
Job Summary:-
JOB TITLE: DATA ENGINEER
CAREER LEVEL: D2
Leverage technology to impact patients and ultimately save lives
Do you have expertise in, and passion for, information technology? Would you like to apply your expertise to impact the IT strategy in a company that follows the science and turns ideas into life changing medicines? If so, AstraZeneca might be the one for you!
ABOUT ASTRAZENECA
AstraZeneca is a global, science-led, patient-focused biopharmaceutical company that
focuses on the discovery, development and commercialisation of prescription medicines for some of the worlds most serious disease.
But were more than one of the worlds leading pharmaceutical companies.
At AstraZeneca were dedicated to being a Great Place to Work.
ABOUT OUR IT TEAM
Its a dynamic and results-oriented environment to work in but thats why we like it.
There are countless opportunities to learn and grow, whether thats exploring new technologies in hackathons, or redefining the roles and work of colleagues, forever.
Shape your own path, with support all the way.
Diverse minds that work cross- functionally and inclusively together.
ABOUT THE ROLE
We are looking for a Data Engineer to help us build intelligent applications that make use of our structured and unstructured data to derive key insights.
As part of the R&D Data Foundation engineering group you will work together with ML engineers and data scientists to build the data foundations supporting R&D.
We are building a global Competitive Intelligence platform that will provide industry leading competitive intelligence across our R&D and Commercial organisations.
As a member of our team, you will be primarily responsible for implementing ETL processes.
You should be well-versed in the design and development of ETL and database developments for large data products, as well as maintaining and supporting production environments.
Part of a DevOps team implementing and supporting ETL workflows.
Data sources will be: structured, semi-structured and unstructured.
Working with suppliers, data scientists, machine learning engineers, and platform teams to acquire and process data.
Analysing data requirements, source data, model the source, and determine the best methods in extracting, tra
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