Sr. DevOps Engineer
Budget: ₹150,000 – ₹250,000 INR
Job Description
About The Position:
The Risk & Analytics Department lives at the core of the business model — figuring out how to take smart risk that allows for a smooth and empowering experience for all legitimate users, while also preventing fraud and protecting the company’s bottom line.
The Data Science Foundations team is responsible for building and maintaining the data infrastructure and analytical tooling that enables teams of data scientists and analysts at Client.
We are looking for a Senior DevOps engineer to help design and implement the next generation of infrastructure for data science at Client.
Your Duties & Responsibilities:
Work in cross-functional teams with Product managers, data engineers, data scientists to
create robust and scalable infrastructure to enable data science at scale.
Be responsible for building, improving, maintaining, and standardizing the build pipelines
of our ETL, analytics, and ML-related services, so that we can experiment with confidence,
reducing the time, it takes to go from ideation to production.
Advise our team of engineers on how to best set up the infrastructure for ETL and
machine-learning projects.
Setup and document best practices for the development of new infrastructure and software
projects.
Collaborate with cybersecurity experts, data governance officers, and SREs to ensure our
analytical infrastructure is secure and robust.
Qualifications/Must Have:
Is able to work with non-experts, understand their needs, and build infrastructure and
tooling to support.
Can communicate complex technical concepts clearly to non-experts
Has extensive experience designing, deploying, and maintaining infrastructure in AWS,
including but not limited to network management, S3, RDS, EMR, Glue, and more
Has extensive experience with Python software development
Has extensive experience with CI/CD technologies such as CircleCI, Jenkins, etc…
Please be advised that you download the similar App, such as Klarna, Afterpay, Affirm and so forth, and come up with your opinions on these applications and services.
Nice to have
Prior experience as a data engineer, software engineer, or data scientist
Experience working in data scientist teams as a DevOps supporting ML learning and ETL
projects.
Experience deploying infrastructure in highly regulated environments such as financial
services, medicine, and government agencies.
Experience with standard Python/R data science tooling and libraries such as JupyterHub,
conda, pandas, Shiny, etc…
Conversational Japanese is nice to have but not required.
About The Position:
The Risk & Analytics Department lives at the core of the business model — figuring out how to take smart risk that allows for a smooth and empowering experience for all legitimate users, while also preventing fraud and protecting the company’s bottom line.
The Data Science Foundations team is responsible for building and maintaining the data infrastructure and analytical tooling that enables teams of data scientists and analysts at Client.
We are looking for a Senior DevOps engineer to help design and implement the next generation of infrastructure for data science at Client.
Your Duties & Responsibilities:
Work in cross-functional teams with Product managers, data engineers, data scientists to
create robust and scalable infrastructure to enable data science at scale.
Be responsible for building, improving, maintaining, and standardizing the build pipelines
of our ETL, analytics, and ML-related services, so that we can experiment with confidence,
reducing the time, it takes to go from ideation to production.
Advise our team of engineers on how to best set up the infrastructure for ETL and
machine-learning projects.
Setup and document best practices for the development of new infrastructure and software
projects.
Collaborate with cybersecurity experts, data governance officers, and SREs to ensure our
analytical infrastructure is secure and robust.
Qualifications/Must Have:
Is able to work with non-experts, understand their needs, and build infrastructure and
tooling to support.
Can communicate complex technical concepts clearly to non-experts
Has extensive experience designing, deploying, and maintaining infrastructure in AWS,
including but not limited to network management, S3, RDS, EMR, Glue, and more
Has extensive experience with Python software development
Has extensive experience with CI/CD technologies such as CircleCI, Jenkins, etc…
Please be advised that you download the similar App, such as Klarna, Afterpay, Affirm and so forth, and come up with your opinions on these applications and services.
Nice to have
Prior experience as a data engineer, software engineer, or data scientist
Experience working in data scientist teams as a DevOps supporting ML learning and ETL
projects.
Experience deploying infrastructure in highly regulated environments such as financial
services, medicine, and government agencies.
Experience with standard Python/R data science tooling and libraries such as JupyterHub,
conda, pandas, Shiny, etc…
Conversational Japanese is nice to have but not required.