Backend Engineer, Growth and Data
Join hebbia-ai as a Backend Engineer focused on the intersection of product growth and data infrastructure. You will be integral to building the systems that power our decision-making around user acquisition, feature adoption, and overall business expansion. Key responsibilities include designing and maintaining complex ETL pipelines, creating high-throughput data APIs for analytics consumers, and optimizing data warehousing solutions (like Snowflake or BigQuery). The role requires a deep understanding of product analytics concepts combined with strong backend engineering skills. You will translate business questions into technical requirements, ensuring that the data available to Product and Growth teams is accurate, timely, and actionable. This position impacts company-wide strategy by building the foundational data layer for growth initiatives.
(تازہ ترین نوکریاں، سلیبس اور ٹیسٹ کی تیاری کی مکمل معلومات)
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1900
Fragensatz
220
Dauer
Permanent
Schwerpunkte
People Also Ask (FAQs)
What is the last date to apply for Backend Engineer, Growth and Data?
The closing date is listed in the official advertisement — apply as early as possible.
How do I apply for Backend Engineer, Growth and Data?
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 ashby 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 Backend Engineer, Growth and Data 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: Backend Development, Data Engineering, Growth Metrics, SQL/NoSQL, Analytics Pipelines.
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