• US Citizen

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• Corp-Corp

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• UG :- - Not Required

• PG :- - Not Required

• No of position :- ( 1 )

• Post :- 27th Jul 2022

The AWS Data Engineer designs and develops scalable data solutions using data integration tools and technologies. Being Data Engineer utilizes big data computation, data platforms and storage tools to create prototype and data products. Conduct build and testing of data pipelines and solutions. Additionally, Data Engineer integrates, tests data pipelines with Advance Analytics and AI platforms. Must be proficient with multiple data engineering and integration tools such as Python, Informatica IICS, Spark, Dynamo DB etc. in the AWS environment. 

Profile Description:
The data engineer builds high quality data pipelines driving analytic solutions. The role requires deep understanding of data architecture, data engineering, data analysis, reporting, and a basic understanding of data science techniques and workflows. The ideal candidate is a skilled data / software engineer with experience creating data products supporting analytic solutions.

Responsibilities:
•    Design, develop, optimize, and maintain data architecture and pipelines that adhere to data integration principles and business goals
•    Solve complex data problems to deliver insights that helps our business to achieve their goals
•    Create data products for analytics and data scientist team members to improve their productivity
•    Code, test, and document new or modified data systems to create robust and scalable applications for data analytics
•    Ensure that data pipelines are scalable, repeatable, and secure, and can serve multiple users within the company
•    Enable big data and batch/real-time analytical solutions that leverage emerging technologies
•    Foster a culture of sharing, re-use, design for scale stability, and operational efficiency of data and analytical solutions
•    Lead the evaluation, implementation and deployment of emerging tools and process for analytic data engineering in order to improve our productivity as a team
•    Develop and deliver communication and education plans on analytic data engineering capabilities, standards, and processes
•    Work with Data Science practitioners and developers to make sure that all data solutions are consistent
•    Partner with Business Analysts and Solutions Architects to develop technical architectures for strategic enterprise projects and initiatives.
•    Ensure all automated processes preserve data by managing the alignment of data availability and integration processes
•    Interact with business clients, understand business requirements, propose and deliver data solutions to meet the business requirements.
 
Knowledge & Experience:
•    Bachelor of Science in Computer Science, Engineering, Mathematics, Statistics or related subject
•    2-5 years of experience in Data platforms and technologies in AWS Cloud environment such as Spark, Informatica IICS, Redshift, Postgres, Dynamo DB, Neptune DB, EMR, Glue, Kafka.
•    Expertise in SQL and data analysis and experience with Python and other programming languages
•    Experience developing and maintaining data warehouses in big data solutions
•    Experience with BI tools such as Tableau, Power BI
•    Conceptual knowledge of data and analytics, such as dimensional modeling, ETL, reporting tools, data governance, data warehousing, etc.
•    Exposure to machine learning, data science, computer vision, artificial intelligence, statistics, and/or applied mathematics
•    Demonstrated experience with agile or other rapid development methods
•    Excellent problem solving, critical thinking, quick learning and communication skills
•    Passion for innovation and "can do" attitude to thrive in a fast-paced environment

Additional Qualifications:
•    Expertise in AI, Advanced Analytics and Machine Learning technologies, used SageMaker is a plus
•    Life insurance industry domain experience is a plus.
•    Front-end software development experience is a plus