Top Data Engineering Firms

As we live in the digital world, we find data everywhere. A study by Statista states that there will be 30.9 billion units of connected devices, such as the Internet of Things (IoT), by 2025. This number is roughly 13 billion more than what was expected. That means there is going to be a lot of data, and you need something to collect, store, analyze, and organize that data to be helpful. That's where data engineering jumps in, helping businesses get insightful data and make the best use of it. It involves data engineers who are specialized computer scientists to make the data usable to you.

Data engineers are helpful for business organizations for a variety of reasons. First off, any modern business that receives a large volume of data on a daily basis needs data engineering solution to manage and process that data efficiently. You need insight from the data, which will be possible only if you efficiently collect, store, and process that data.  Data engineering makes things right by helping you transform raw data into usable formats. It can be a boon as you can make data-driven decisions and add value to your business growth.

For big tech companies, data is their lifeblood. They have dedicated data engineers who manage and optimize data for various applications. The first thing they do is build scalable data pipelines. The sole purpose of the pipeline is to collect, store, and process data from as many sources as they have. Technology companies use door data for multiple purposes, like creating valuable features for users, enhancing User experience, and making informed decisions. Let's take some real-life examples of how top tech giants like Google, Amazon, and Facebook (Meta)  are making the best out of data engineering:

• Google uses data engineering to empower search engines and YouTube.
• Amazon uses data engineering to help users with personalized recommendations and manage and optimize logistics and inventory.
• Facebook, on the other hand, uses data engineering for various purposes, including ad targeting, personalization of content, and analyzing user behavior.

A data engineering company can help you with a range of services that are designed to help you make the best use of data. Some of the top services can be developing data pipelines, creating data warehousing, data integration, cloud data engineering, machine learning infrastructure, real-time data processing, and more. You must talk to your data engineering company if you have any particular requirement.

Are you running a company that collects and receives large volumes of data on a daily basis?  Then you must hire a data engineering experts for several important reasons, such as;

• Effective implementation of best practices
• Build a scalable solution so you can cope with increasing volumes and complexity
• Streamline data pipelines to access valuable insights whenever you need
• Cost-effective method to maintain data in the first structure
• Allow your data engineering solution provider to manage your data while you stay focused on your core business objectives and functions
• Access to expertise along with advanced tools and technology to manage, store, and process your data

Before you choose a data engineering services providing company, you need to explore, understand, and analyze your needs. Based on your requirements, you can begin with the steps given here;

• Check experience and evaluate exercises to ensure they can handle your project efficiently.
• Do they offer the service you need?  You can explore their offerings to see if the service you need is mentioned.
• Are your dedicated data engineers familiar with tools and technology?  You need to ensure they can work with your existing system and database.
• Check their case studies to see if they have experience with similar projects.
• You can also explore client testimonials to see if they have received any or a number of positive reviews from clients.
• Do they provide support and maintenance services when the project is over?  Discuss this with your shortlisted data engineering company.

For data engineering, there are hundreds of tools, though not all tools are required to complete the job. The top standard tools that most data engineers use are Apache Kafka, Apache NiFi, Flume, Amazon Redshift, Google BigQuery, Snowflake, Apache HBase, Cassandra, Azure Synapse Analytics, ETL (Extract, Transform, Load) tools, Prefect and Luigi, and many others. You can ask your data engineering service provider if they use the required tools.

Data engineer charges $50 to $300 per hour, though the actual costs depend on three main things, such as;

• Expertise
• Location
• The project's technical demands

Some data engineering companies charge project-wise, and it can be anywhere between $10,000 to $20,000 for small projects, $20,000 to $50,000 for medium-sized projects, and $100,000 for complex projects. You may also talk to data engineering companies if they provide services as a monthly retainer. If yes, the average cost would range between $5,000 to $25,000.