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| Job Location | Delhi |
| Education | Not Mentioned |
| Salary | Not Disclosed |
| Industry | KPO / Analytics |
| Functional Area | General / Other Software |
| EmploymentType | Full-time |
Description
Lead Data Engineer-Chegg Web Services Job Location-New Delhi, India
The organization: Data Engineering The Data Engineering team is central to Chegg supporting every business line and functional organization at the company. It is a team composed of data engineers and architects. The team influences strategy and tactics for Chegg s data ecosystem. The role: Lead Data Engineer Lead Data Engineer will be responsible to extract, model, transform and store Students daily interactions with Chegg s physical and digital books, subscriptions, and learning aids generate terabytes of structured and unstructured data. The data will be used by scientists and analysts looking for patterns in how students are learning from our products and services. The data will drive business decisions and future investments. The data will transform education Chegg is your sandbox to make this happen. As a Lead Data Engineer, you will execute the strategy and roadmap for data engineering at Chegg. You will define, evolve and mature Chegg s existing data platform and processing framework that handles terabytes of data from our various properties. You will work with a team of data engineers, analytics and data scientist teams to identify the needs and contribute towards building the next generation data ecosystem at Chegg. You will engage with analysts and leaders to research and develop new data engineering capabilities. The responsibilities:
Technical leader at Chegg for Data Engineering with a core focus on AWS technical architecture.
Define, design and build data frameworks (ingestion, processing, distribution, access) for Chegg s big data based data platform.
Drive design and build for scalable events processing framework that handles billions of events and terabytes of data.
Drive design and build for robust and scalable data engineering solutions for structured and unstructured data conducive to business insights, reporting, and analytics.
Design and implement data models that scale across the enterprise.
Work closely with stakeholders (Reporting team, Analysts, and Business) and source system domain experts.
The requirements:
10+ years experience working as an engineer in a data-focused team building data processing frameworks and capabilities using the AWS technology stack. End to end experience in alternative tech stacks (Kafka etc.) will also be considered as a plus.
Deep expertise in AWS technical stack : chiefly Lambda, S3, EC2, ECS, EMR, DynamoDB, Redshift amongst others . A large percentage of the role is to drive the design and implementation of Chegg s next generation data platforms.
Extensive experience working with structured and unstructured data.
Experience with design and implementation of end-to-end event pipelines.
Expertise in utilizing scripting/programming skills like Java, Perl, Python for Large-scale data processing.
,Keyskills :
sqljava data warehousinginformatica pythonbig data data modelsweb services team buildin