Netflix Taggers Job $/22 Hour

Netflix; Cheyenne (WY); On-site; USD 26,000 - 34,000; Full time

Job summary

Netflix in Cheyenne, USA is seeking a Software Engineer with strong Python data tooling and GraphQL experience. You will work on data platforms, APIs, and analytics supporting data engineers and scientists. A graduate-level education is expected.

The role emphasizes building scalable data infrastructure, collaborating with cross-functional teams, and driving data-driven decision making across the organization.

Qualifications

• Proficient Python with data tooling experience.
• Strong data analysis and problem solving with cross-functional teams.
• Familiarity with building data-driven products and pipelines.

Responsibilities

• Handle data engineering tasks at scale and contribute to data tooling.
• Collaborate with data scientists and engineers to improve analytics platforms.
• Contribute to the design and evolution of the data stack and APIs.

Skills

Python

Data analysis

Team collaboration

Education

Graduate

Tools

GraphQL

Jupyter

TensorFlow

Looker

Job description

Job Information

Job Responsibilities: Software Engineer Salary: $/22 Hour Company: Netflix Location: Cheyenne, USA Educational Requirements: Graduate

Full Job Description

At Netflix, we want to connect with the world and are ceaselessly upgrading on how redirection is imagined, made, and passed on to an overall group. We at present stream content more than 30 tongues in 190 countries, outmaneuvering more than 220 million paid allies and are wandering into new kinds of redirection like gaming. The Data Stage bunches at Netflix engage us to utilize data to get joy to our people in different ways. We give brought together data stages and instruments for various business capacities at Netflix, so they can utilize our data to go with fundamental data-driven decisions. We do all the genuinely troublesome work to simplify it for our associates to work with data capably, securely, and competently. We look to beat the competition standard in building a tip-top data establishment, as Netflix drives the technique for being the most renowned and undeniable target for overall web redirection. The mission of the Data Stage Scratch cushion and APIs bunch is to help the effectiveness of the data science and planning neighborhood Netflix. This suggests enabling clients to contribute more energy doing what needs to be done issues and less time planning lower-level structures. We outfit our inside clients with a changed type of Jupyter Scratch cushion, as well as Python APIs that license them to consequently get to the data stage. The Python Programming point of interaction gives programmed induction to the Data Stage, enabling clients to address data, help out tables, move data, and direct pack occupations and work processes. Close to the front, we use a blend of JavaScript developments and continuously rely upon the Answer framework and JupyterLab extensions. On the backend, we have gathered organizations and shows using Scala, GraphQL, Node.js, and Python. As a person from the Notebooks and APIs bunch, your work will directly impact the effectiveness of our data engineers, data scientists, and artificial intelligence engineers. We are searching for an expert to add to the turn of events and headway of our data assessment devices. We are centered around building an alternate and extensive gathering to bring new perspectives as we tackle the accompanying plan of hardships.

Key Responsibilities

• Handling real business needs at a large scale by applying your programming and logical decisive reasoning skills.
• Unequivocally enlivened by data assessment and lively about building contraptions for data analysts and simulated intelligence engineers.
• Driving cross-reasonable drives and cooperating with engineers, thing chiefs, and TPM across gatherings.

About You

• You are an expert in Python, and have expansive contributions to Python pack-the-board tooling.
• Experience with GraphQL joining and progression.
• Experience in building and working adaptable, issue-merciful, appropriate systems.
• Experience with any of these spaces: Data science (e.g., Jupyter Scratch cushion, pandas, numpy), simulated intelligence (e.g., TensorFlow, PyTorch, sci-kit-learn) an enormous notwithstanding.
• Experience in enormous data headways and coordination gadgets (e.g Streak, Presto/Trino, Druid, Snowflake) a huge notwithstanding.
• Experience with insight gadgets like Scene and Looker at least an.
• Experience building front-end applications (Answer, Center point, etc) at least an.