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Stripe

Software Engineer, Data Orchestration

Are you passionate about building the backbone of massive-scale data infrastructure? As a Software Engineer in Data Orchestration at Stripe, you will be instrumental in designing, developing, and maintaining resilient, high-throughput data pipelines that power core financial services. Key responsibilities include implementing robust workflow management systems using tools like Apache Airflow, optimizing ETL/ELT processes for petabyte-scale datasets, and ensuring data lineage integrity across multiple microservices. The ideal candidate possesses deep expertise in Python, distributed systems, and cloud infrastructure (AWS/GCP). You will collaborate with senior engineers to solve complex data consistency challenges, transforming raw transactional data into reliable, actionable insights used globally by millions of businesses.

Stripe N/A, United States

(تازہ ترین نوکریاں، سلیبس اور ٹیسٹ کی تیاری کی مکمل معلومات)

bereiten sich vor

1200

Fragensatz

150

Dauer

Permanent

Schwerpunkte

Data PipelinesETL/ELTAirflowScalabilityPython

People Also Ask (FAQs)

What is the last date to apply for Software Engineer, Data Orchestration?

The closing date is listed in the official advertisement — apply as early as possible.

How do I apply for Software Engineer, Data Orchestration?

Use the official apply link on this page to submit your application. A step-by-step how-to-apply guide for this job is also linked below.

Is there negative marking in the Stripe test?

The marking rule is announced per test in the advertisement and roll-number-slip instructions. Many MCQ screening tests have no negative marking, but always verify it for your specific test.

What is the passing marks for this test?

The official passing marks are generally 50%, but merit is competitive — scoring above 75% is a safer target to secure an interview call.

How can I prepare for the Software Engineer, Data Orchestration test?

Prepare with the free subject-wise MCQs, past papers and timed mock tests on PrepPro Academy — every question includes the answer with an explanation. Focus areas: Data Pipelines, ETL/ELT, Airflow, Scalability, Python.

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