Sr. Data Engineer

at ERUDITUS Executive Education

Sr. Data Engineer

ERUDITUS Executive Education

Company

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Sr. Data Engineer

at ERUDITUS Executive Education

Posted by Payal Thakker

3 - 10 yrs

₹15L - ₹45L / yr

Remote only

Skills

Docker

Kubernetes

Apache Kafka

Apache Beam

Python

Machine Learning (ML)

Data Analytics

Emeritus is committed to teaching the skills of the future by making high-quality education accessible and affordable to individuals, companies, and governments around the world. It does this by collaborating with more than 50 top-tier universities across the United States, Europe, Latin America, Southeast Asia, India and China. Emeritus’ short courses, degree programs, professional certificates, and senior executive programs help individuals learn new skills and transform their lives, companies and organizations. Its unique model of state-of-the-art technology, curriculum innovation, and hands-on instruction from senior faculty, mentors and coaches has educated more than 250,000 individuals across 80+ countries. Founded in 2015, Emeritus, part of Eruditus Group, has more than 2,000 employees globally and offices in Mumbai, New Delhi, Shanghai, Singapore, Palo Alto, Mexico City, New York, Boston, London, and Dubai. Following its $650 million Series E funding round in August 2021, the Company is valued at $3.2 billion, and is backed by Accel, SoftBank Vision Fund 2, the Chan Zuckerberg Initiative, Leeds Illuminate, Prosus Ventures, Sequoia Capital India, and Bertelsmann.

As a data engineer at Emeritus, you'll be working on a wide variety of data problems. At this fast paced company, you will frequently have to balance achieving an immediate goal with building sustainable and scalable architecture. The ideal candidate gets excited about streaming data, protocol buffers and microservices. They want to develop and maintain a centralized data platform that provides accurate, comprehensive, and timely data to a growing organization

Role & responsibilities:

Developing ETL pipelines for data replication
Analyze, query and manipulate data according to defined business rules and procedures
Manage very large-scale data from a multitude of sources into appropriate sets for research and development for data science and analysts across the company
Convert prototypes into production data engineering solutions through rigorous software engineering practices and modern deployment pipelines
Resolve internal and external data exceptions in timely and accurate manner
Improve multi-environment data flow quality, security, and performance

Skills & qualifications:

Must have experience with:
virtualization, containers, and orchestration (Docker, Kubernetes)
creating log ingestion pipelines (Apache Beam) both batch and streaming processing (Pub/Sub, Kafka)
workflow orchestration tools (Argo, Airflow)
supporting machine learning models in production
Have a desire to continually keep up with advancements in data engineering practices
Strong Python programming and exploratory data analysis skills
Ability to work independently and with team members from different backgrounds
At least a bachelor's degree in an analytical or technical field. This could be applied mathematics, statistics, computer science, operations research, economics, etc. Higher education is welcome and encouraged.
3+ years of work in software/data engineering.
Superior interpersonal, independent judgment, complex problem-solving skills
Global orientation, experience working across countries, regions and time zones

Emeritus provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Role & responsibilities:

Developing ETL pipelines for data replication
Analyze, query and manipulate data according to defined business rules and procedures
Manage very large-scale data from a multitude of sources into appropriate sets for research and development for data science and analysts across the company
Convert prototypes into production data engineering solutions through rigorous software engineering practices and modern deployment pipelines
Resolve internal and external data exceptions in timely and accurate manner
Improve multi-environment data flow quality, security, and performance

Skills & qualifications:

Must have experience with:
virtualization, containers, and orchestration (Docker, Kubernetes)
creating log ingestion pipelines (Apache Beam) both batch and streaming processing (Pub/Sub, Kafka)
workflow orchestration tools (Argo, Airflow)
supporting machine learning models in production
Have a desire to continually keep up with advancements in data engineering practices
Strong Python programming and exploratory data analysis skills
Ability to work independently and with team members from different backgrounds
At least a bachelor's degree in an analytical or technical field. This could be applied mathematics, statistics, computer science, operations research, economics, etc. Higher education is welcome and encouraged.
3+ years of work in software/data engineering.
Superior interpersonal, independent judgment, complex problem-solving skills
Global orientation, experience working across countries, regions and time zones

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About ERUDITUS Executive Education

Founded :

2010

Type :

Services

Size :

1000-5000

Stage :

Raised funding

About

Emeritus provides online business and professional programs in collaboration with top universities from across the globe

Loyson Mascarenhas

Connect

Company social profiles

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