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CUSTOMER ENGINEERING

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Onsite

CUSTOMER ENGINEERING

Unicorn Infotech Consulting Services

CUSTOMER ENGINEERING

Skills

Big DataMongoDBReactNodeGolangJavaReact NativePostgreSQLKafkaRedisScalaAWSOracleFinancial AnalysisAzure

6 months ago

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Important information


Contract type:

Permanent

Location:

Bengaluru, Karnataka, India

Work mode:

Onsite

Published on:

15 August 2026

What they need


Company : NUMBERZ

Experience : 4 to 10 Years

Location : Bangalore

Skill set : FINANCE, CUSTOMER ENGINEERING

Who Are We Finance! Taxes! Payments! Sounds interesting, right? Wrong! No business enjoys the grueling aspects of handling their finances. That’s where we come in!

numberz is a SaaS platform that simplifies the most important aspect of a small business& life — their cashflow. We’re a team of ambitious, driven professionals with a wealth of experience in Financial Technology, and we’re looking for people who share our enthusiasm to solve problems plaguing the Indian economy.

No. of employees: Overall – 30, Product & Engineering – 10

Location: Bangalore

Domain We Work In Accounts Receivables – Finance.

Who Do We Want As a Member of Customer Engineering team act as the key point of contact for our clients during the initial phases of customer onboarding and occasional tactical requirements. As a member of this dynamic team, you will bring a strategic mindset to projects and spend time understanding, educating and negotiating with clients in order to bring a sustainable and efficient technical vision to life. Having a balance of high-level and tactical mindsets is a must, as you will spend time both with

clients and alongside your fellow teammates.

On Data – We Would Like You To  Understand data – data models, formats, structures and see through to get to the semantics with an eye for simplification, processing and automation

 Exposure to various ETL concepts and data activities – cleansing, standardization,

enrichment, map/reduce, workflows, pipelines and integration

 Exposure to algorithms and processing techniques handling large data sets

On Engineering – We Would Like You To Have  Hands-on experience in back-end & fine-tuning of applications, latency avoidance and optimization techniques

 Solid understanding of micro-services and experience in consuming and building extensible REST APIs

 Experience in the design and development of reusable components

 Experience engineering software systems of large scope and complexity

 Experience with building applications for AWS/Azure based cloud domains

 Knowledge of Database technologies (e.g. RDBMS like Oracle or Postgres)

 A deep passion for software engineering and getting stuff done using pragmatic approaches to iterate towards solutions for hard problems

If Hired, What You Would Do At Numberz Numberz AR is an enterprise SaS platform and demands enterprise grade approaches and solutions to work with various ERPs. The Engineering around managing the data that goes into the platform is very high and critical to ensure smooth delivery of platform capabilities. We believe in automation and reusability of everything we build, so that we continue to solve new and more interesting

problems. It is all about Data, Automation and Smart Coding.

In essence, you will be bending the spoon to make anything possible.

Requirements – Must have strong experience with Clojure

– Good working knowledge with PostgreSQL, MongoDB, Redis

– Experience in Node.js, Golang, Java/Scala, React/React-native/Redux

– Exposure to Distributed Streaming Platforms (Kafka preferably)

Who Should Join Us If any of the following apply to you, hit us up:

  • You’d like to work on sophisticated distributed software that solves for complex financial workflows.
  • You want to work with fun folks who are also steeped in customer-driven product

development.

  • You like autonomy, and the freedom to come up with solutions that solve the problem best. Regardless of the technology.
  • You believe in the power of data to solve previously unsolved problems. More specifically, problems pertaining to predictive financial analysis.

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