About the role
This is a remote position.
Please go through the entire job post thoroughly before pressing Apply. Post pressing Apply, you shall reach the assessment page that must be attempted.
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Busigence is a Decision Intelligence Company. We create decision intelligence products for real people by combining data, technology, business, and behaviour enabling strengthened decisions.
Fresher - Big Data Engineer
Team: Engineering
Location: Remote
Relevant Exp: 0-2 Years
Background: Been there-Done that
Compensation: Above industry standards
Requirements
This is an immediate requirement. We shall have an accelerated interview process for fast closure - you would required to be proactive and responsive
Remote position (work-from-anywhere)
Immediate joiners must apply
Data Engineering Experienced - course/competitions/internships/job (<2 years)
Competitive compensation
************ | MUST HAVE | ************
1. Code in Python3 - Numpy?
2.Code in Python3 - Pandas?
3.Developed data engineering pipelines on real-world problem (not just academic projects)?
4.Implemented advanced SQL queries
5.Developed complex logics in Python3
6.Confidence to learn PySpark3 within a month?(we shall guide but won't spoon-feed)
OR
Confidence to learn Kafka3 within a month? (we shall guide but won't spoon-feed)
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We are offering one of the most challenging & exciting work on Data Pipelines. You shall be working on sophisticated platforms, products and applications
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We are looking for developer with real passion for data ingestion, data transformation and data management. This is aspecialistandindividual contributorrole.Product developmentexperience preferably ata startup or a lean teamis desired
ROLE
Mandatory
1. Building data acquisition pipelines ingesting data from various source systems (databases, flat files, software, APIs)
2. Building data munging pipelines transforming data format, shape and value
3. Must be able to convert, break, & distribute existing Python codes to functional programming syntax
4. Must be able to execute data structures, linear algebra and algorithms implementation at scale on parallel/distributed clusters
5. Must be able to recognize code that is more parallel, and less memory constrained, and you must show how to apply best practices to avoid runtime issues and performance bottlenecks
Preferred
1. Functional programming in Python on vinaigrette map-reduce lambda paradigm
2. Knowledge of first-class, high order, & pure functions, recurisons, lazy evaluations, and immutable data structures
Benefits
How to Apply You should apply online by clicking "Apply Now". For queries regarding an open position, please write
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Scaling established startup innovating & disrupting various domains through artificial intelligence. We bring those people onboard who are dedicated to deliver wisdom to humanity by solving the world’s most pressing problems differently thereby significantly impacting thousands of souls, everyday. We are a deep rooted organization with success story having worked with folks from top tier background (IIT, NSIT, DCE, BITS, IIITs, NITs, IIMs, ISI etc.) maintaining an awesome culture with a common vision to build great data products. In past we have served fifty five customers and presently developing Enterprise AI products. More details at
We work extensively & intensely on big data, data science, machine learning, deep learning, reinforcement learning, data analytics, natural language processing, cognitive computing, and business intelligence.
We look for intent & talent, not skills 1. You must be [super sharp] 2. You must be [extremely energetic] 3. You must be [honourably honest] In addition to the regular stuff which every good startup offers – Lots of learning, Food, Parties, Open culture, Flexible working hours, and what not….
We offer you:[Greatest work of life]
You shall be working on our revolutionary products which are pioneer in their respective categories. This is a fact.
We try real hard to hire fun loving crazy folks who are driven by more than a paycheque. You shall be working with creamiest talent on extremely challenging problems at most happening workplace
Originally posted on Himalayas