Hire remote enterprise MongoDB developers

Get the enterprise-level freelance MongoDB developers you need. Fast. Torc takes the pain out of finding highly-productive enterprise MongoDB developers.

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Hire MongoDB developers

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What is an enterprise MongoDB developer?

MongoDB is a non-relational, document-based, cross-platform database. It was developed in 2007 by the software company 10gen.  It started initially as a platform-as-a-service (PaaS) product. In 2009, it became open-sourced as it began offering commercial products and services. In 2013, 10gen changed its name to MongoDB Inc.

MongoDB is designed to store large amounts of data and work efficiently with them. It is called a NoSQL database because data is stored and retrieved through collections and documents and   not through tables, rows, and columns.

MongoDB is great for projects that need to store large amounts of complex data, manage and deliver content, and manage user data.

The support system for MongoDB is quite large, as it supports a lot of programming languages like Node.js, PHP, Python, Net, Go, Java, C, C++, Perl, and Ruby, among others. MongoDB is widely preferred over relational databases due to the following advantages:

  • MongoDB enables great flexibility with the database. It is a schema-less database that allows one collection to hold different documents in a collection with a different number of fields, content, and size.
  • MongoDB is much faster in performance compared to a Relational Database Management System.

How to hire MongoDB developers FAQ

MongoDB hiring guide

When hiring a MongoDB developer, you need someone who is fast and efficient. They should be able to use the features that come with MongoDB to get to the data faster and more efficiently. They must understand JavaScript, Python, or Java, as well as have extensive hands-on experience with MongoDB.

A MongoDB developer should be familiar with cloud platforms like Azure, AWS, and GCP. They should know how to design relational databases and handle the deployment of databases on these cloud platforms.

In terms of experience, skills, and knowledge, the following levels exist:

  • An entry-level MongoDB developer is someone who is relatively new to MongoDB but has some background in managing NoSQL databases. They might not be able to comprehend why other types of databases are inadequate for the work they do. They should be able to use MongoDB to create collections and documents and work with representation and query techniques. 
  • An intermediate MongoDB developer is someone who is familiar with the various MongoDB concepts. They ought to be able to model relationships, set up dependencies, and connect MongoDB with a preferred MongoDB driver such as mongoose. They should also be able to design a MongoDB schema.
  • A senior MongoDB developer is someone with in-depth knowledge of MongoDB and experience managing high-level interactions with MongoDB. They are able to maintain current applications as well as integrate innovative features into new products and applications. A full stack MongoDB developer typically uses the MERN or the MEAN stack.

When hiring a MongoDB developer, there should be more than one step to check the candidate's technical skills, experience, and fit with the role and team. Possible hiring procedures include the following:

  1. Examining the applicant's application and resume to see if they satisfy the position's fundamental requirements
  2. Initial phone or video interview to discuss the candidate's background, experience, and interests, as well as to provide additional information about the company and the position.
  3. A technical evaluation, such as a coding assessment or a technical interview, to evaluate the candidate's technical skills and knowledge is given.
  4. An onsite/ virtual meeting with the candidate, potential manager, and team to discuss the candidate's experience and qualifications for the role and team, as well as their compatibility with the team.
  5. Verification of a candidate's experience and qualifications through checking of references.
  6. Final offer made to the chosen candidate.

MongoDB job description template

As a MongoDB developer at [Company], you will take care of MongoDB databases and work to improve their performance, security, and availability. Your responsibilities will include:

  • Collaborate with the development teams to add new features to new products and apps and keep old ones running. 
  • Write scripts to automate daily tasks while maintaining the security of your data sets.
  • Contribute to code reviews and offer constructive feedback to team members.
  • Assist the team in identifying and diagnosing technical issues and in resolving them.
  • Keeping up-to-date with the latest developments in MongoDB and related technologies.

Requirements:

  • Strong experience with a programming language commonly used with MongoDB (such as JavaScript, Python, or Java) is required.
  • Understanding of database management systems
  • Knowledge of either Mongoose or any other standard MongoDB driver.
  • Ability to configure schema and MongoDB data modeling
  • Expertise in MongoDB installation and administration on AWS and Red Hat
  • Detailed knowledge of the MongoDB architecture
  • Experience designing systems that manage large data sets and a massive volume of transactions.
  • Expertise in database security administration
  • Excellent analytic and problem-solving skills
  • Strong communication skills, the ability to work well in a team, and the ability to problem-solve and troubleshoot

MongoDB interview questions

Here are five questions that can be asked during a technical interview with MongoDB.

Question 1: How are queries performed in MongoDB?

This is a great question to find out the different ways a developer applies filtering to MongoDB queries in a project. A great response would be, "Querying can be done in MongoDB using the find method; however, the selection criteria are based on the query parameter passed in the find method." 

Code snippets could also be given for some of the criteria specified.

A good response would be to describe the process of querying without mentioning the selection criteria. As the interview goes on, the interviewer can ask how to filter and describe exactly what is being returned as results.

Question 2: What are indexes in MongoDB?

With this question, the interviewer wants to know if the developer understands the impact of the indexes, how indexes work, and how they are implemented in MongoDB. A good answer will be:

Indexes are structures in MongoDB that facilitate effective querying. Without indexes, MongoDB would have to look through every document in a collection to find the ones that match each query. The performance of your application may suffer as a result of these collection scans because they are slow. If you use an index to cut down on the number of documents that MongoDB has to look at, your queries will work better and return faster.

In MongoDB, there are many different types of indexes. The single field and compound index types are the two that are used the most frequently.

The best answer to this question is to include the impact of indexes on memory allocation. Before you build indexes, map out the types of queries you will run so that you can build indexes that reference those fields. Indexes come with a performance cost but are more than worth the cost for frequent queries on large data sets. Think about how often each query is used in the application and whether or not it needs an index.

Question 3: What is the difference between MapReduce and the Aggregation Pipeline in Data Aggregation in MongoDB?

This is a great question to ask to know if the developer understands the importance of efficiency and speed when querying large data sets.

A good answer would be that both methods of data aggregation are used to utilize stages to filter data and perform operations like grouping, sorting, and transforming the output of each operator. The queries for MapReduce are run in a single thread and are based on JavaScript using the SpiderMonkey engine. Aggregation Pipeline queries, on the other hand, are executed using compiled C++ code, which is faster than interpreted JavaScript.

A great answer will include the fact that MapReduce is no longer supported in MongoDB version 5.0 and give code samples for both methods. The developer should be able to write snippets that use the map-reduce method to query data and rewrite the operation as an aggregation pipeline.

A map-reduce operation on the collection of products sorts them by customer_id and figures out the total price for each customer_id:

An aggregation alternative to the map-Reduce operation:

Question 4: What are the important points to consider when creating a schema in MongoDB?

This is a great question for the interviewer to assess the developer's understanding of MongoDB schema design best practices.

Designing a schema that works for your application is one of the most crucial aspects. You can do that by taking into account user requirements, the data you want to store, the query performance, and the hardware that is available. If you intend to use multiple objects together, combine them into a single document; otherwise, separate them.

It is best to avoid creating documents that are likely to grow larger than the allowed default size of 16MB per document. Otherwise, queries may fail. When updating documents, use field modifiers to update only specific fields to avoid performance degradation caused by MongoDB having to rewrite the entire document, perform schema denormalization, and use embedded documents to retrieve the required data in a single query. You can create indexes to sort data, update them when documents are updated, and optimize their use by overriding the default id field.

A good answer will include the fact that a well-designed MongoDB schema is the most important part of setting up a database that is scalable, fast, and cheap.

Question 5: What is sharding in MongoDB?

MongoDB developers are primarily concerned with data storage and manipulation. This is a great question to test the developer's knowledge of data storage in MongoDB.

Sharding is the process of distributing and storing data records across multiple host machines in MongoDB. This helps keep high query rates from putting too much stress on the system and making it hard for users to use. For the sharding procedure, it is necessary to split large data sets into smaller ones.

MongoDB resolves this issue by using the horizontal form of scaling through sharding. Each part of a horizontally split database or search engine is called a "shard." Each shard is a single MongoDB instance, and it contains a sharded data subset. MongoDB creates a sharded cluster of multiple MongoDB instances with Mongo and at least three Config servers. This sharding approach allows MongoDB to scale up to meet data growth demands.

A great answer will include some considerations that need to be made when choosing to shard a data record. Sharded cluster infrastructure requirements and complexity require careful planning, execution, and maintenance.

MongoDB does not provide a way to unshard a sharded collection once it has been sharded.

Enterprise MongoDBdeveloper FAQ

What is the two-week guarantee for Torc MongoDB developers?

The best way to evaluate whether a developer is a great match is by working with them. That's why we make it as easy as possible to get started. If a developer isn't working out within the first two weeks of your engagement, we'll work with you to find a better match and won't bill you for the original developer. It's a no-risk way for you to get the help you need even faster.

How does Torc ensure high-quality MongoDB candidates?

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Can Torc use my company's skill assessment to vet MongoDB developers?

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How much do Torc MongoDB developers cost?

Developers in the Torc community set their own rates. The three primary factors that determine the cost of a Remix developer are:

  1. Experience - Everyone would prefer a senior developer but, let's be honest, 10+ years of experience isn't always required. If you consider the work the developer will be doing and the amount of support within your existing team they'll have access to, you might be better served with one or two junior Remix developers over one senior developer.
  2. Skill mix - Marketplaces operate under normal supply and demand dynamics. Developer rates often increase with more niche, complex, or in-demand skill requirements.
  3. Geography - While remote work has flattened the geographic pay disparity to some degree, where your developer lives does factor into their cost. In 2022, the median rate for Torc developers in Latin America was 29% lower than developers in the U.S., Canada, and Western Europe, while the median rates in Eastern Europe and Asia/Oceania were 24% and 40% lower, respectively.

How do I hire remote MongoDB developers?

Torc simplifies the hiring process for you and for developers, and it all starts with letting us know what you're looking for. If you're a new Torc customer, schedule a meeting with our sales team to discuss your needs and get the paperwork squared away. If you're an exiting customer, you can create a new job opportunity directly in the Torc platform.

Once the job is finalized, our AI matching algorithm and team of technical talent specialists will get to work identifying great candidates from the Torc community. You can review their profiles and assessments, interview shortlisted candidates, and hire the perfect developer - all in under a week.

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