Data Engineer

Data Engineer

  • Anywhere

Company Name:-
Sanofi

Job Location:-
Mumbai, Maharashtra

Job Summary:-
· Mission statements
o Responsible for building the pipelines and tools in the DARWIN environment
o Produce data sets for specific analysis projects, dashboards and applications, and general reuse.

o Identify data engineering needs and implement optimal solutions.

o Provide subject matter expertise to other users who are working in the DARWIN environment.

People
o Maintain effectiveness relationships with the end stakeholders with an end objective to develop education and communication content as per requirement
o Interact effectively with healthcare professional on publications content
o Constantly assist other writers in developing knowledge and sharing expertise
Performance
o Create and maintain optimal data pipelines using Sanofi’s data platform and infrastructure
o Assemble large, complex data sets that meet the needs of data analysts and data scientists as per agreed timelines and quality
o Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

o Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.

o Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics.

o Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.

o Create data tools for analytics and data scientist team members that facilitate their discovery, access and use of data.

Process
o Build processes supporting data transformation, data structures, metadata, dependency and workload management.

o Successfully manipulate, process and extract value from large disconnected datasets.

o Bring Working knowledge of message queuing, stream processing, and highly scalable ‘big data’ data stores.

Stakeholders
o Work with data and analytics experts to strive for greater functionality in our data systems.

o Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data

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