Senior Data Engineer

ERUDITUS Executive Education

Posted: about 2 months ago

Company Website
https://cutshort.io/jo...
Position type
full time
Job source
Cutshort
Category
programming
Remote
No
Salary
30 - 40 lacs/annum
Job location
India
About

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.

 

 

Key responsibilities of the role:

 

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:
  1. Virtualization, containers, and orchestration (Docker, Kubernetes)
  2. Creating log ingestion pipelines (Apache Beam) both batch and streaming processing (Pub/Sub, Kafka)
  3. Workflow orchestration tools (Argo, Airflow)
  4. 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.

 

Skills:- Data Science, Data engineering, ETL management, Docker, Kubernetes, Apache Beam, Apache Kafka, Machine Learning (ML) and Virtualization

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