Hiring a Data Engineers For Your Business: The Definitive Guide

Hiring a Data Engineers For Your Business: The Definitive Guide

During the last few years, more and more businesses have realized the significance of data and its ability to improve all areas of their company, both external and internal. As a result, modern companies need to be data-driven. 

“A company’s ability to compete in the emerging digital economy will need faster-paced, forward-looking decisions. Data and analytics leaders must assert themselves into corporate strategic business planning to guarantee that data and analytics competencies are incorporated within the highest-level public-facing company plans,” says Douglas Laney, distinguished VP analyst at Gartner.

In recent years, the number of data experts has increased. Companies hire data engineers to design and develop the systems and processes that can successfully extract, transform, collect, store and analyze big data. Data engineers can work with different industries and sectors. Thanks to their work, organizations can use data to make better operations decisions and save time and money by providing more targeted information for managers, teams, and clients.

Hiring outstanding data engineers is essential. This guide to hiring a data engineer will help you clearly understand the role, hard skills and soft skills you should consider learning more about future candidates for the position.

What is a Data Engineer?

Data engineers are essential employees of any company’s data analytics team. They are responsible for collecting, optimizing, data warehouse, data managing, and sharing it between the company’s departments. What does a data engineer do? They develop data collection, storage, and analytics solutions and create real-time data pipelines and other data systems. 

In addition, data engineers need to know how to create dashboards, different reports, and other visualizations for companies’ decision-makers. Also, the data engineering team needs to understand a business’s or client’s goals and data strategy to do this.

Why Do You Need a Data Engineer?

The main point of becoming a data-driven organization is that you can use these valuable insights for growth. Using data to comprehend how your clients and company work allows you to employ techniques to grow quickly. 

Learn more about “How to be a data-driven decision-making company in times of crisis”

As your data grows, so does the task of managing it. You need to ensure you can scale for the following demands:

Why Your Company Needs a Data Engineer

All of this can be packaged up into the data engineering role. A Data Engineer can allow your business to scale through the:

  • Fetching data from multiple sources and storing them in one place using on-premises or cloud storage for analytical reporting and strategic decision-making;
  • Consolidating structured and unstructured data from different sources to get a unified view with real-time insights;
  • Creating real-time data streaming platforms, creating data warehouses/lakes, and processing big data.

So, first of all, can you answer questions like:

  • What kind of data is valuable?
  • Where do you store this valuable data?
  • And how do you make the most of it? 

Thus, a data organization strategy should be a top priority when developing an internal data management plan. This includes creating a process for collecting and organizing data (ETL) and assigning roles and responsibilities within your company. 

Sounds like too much work? That’s why your company needs to hire top data engineers.

Guide For Hiring Data Engineer Company

If you’re hesitant about how to hire a data engineer or don’t know where to start, this guide is for you. With the help of this data engineer hiring guide, you’ll learn how to find outstanding engineers who benefit your project, where to find one, how to hire the best team, and much more!

1. Analyze Your Needs

Successfully hiring a remote data engineer team is only possible by understanding precisely what you want from your project. So, first, you should consider all requirements and describe them as an exact specification (SOW):

  • Choose the leading technologies needed for a project to understand the particular type of experience and expertise you require. Below you can read the technologies used by data engineers. This checklist can include, but is not limited to:
  1. Language: Java, Python;
  2. Databases: SQL Server, Oracle, MariaDB, PostgreSQL, Redshift, Clickhouse;
  3. BI tools: Power BI, Power View,  Power Pivot, Performance Point, Tableau, Apache Superset;
  4. Big Data: Flume, Spark, Nifi, Kafka, Flink;
  5. Cloud providers: AWS, Azure, Google cloud.
  • Further, determine the duration and deadline for your project. 
  • Estimate how many skilled data engineers will be required to finish your project within the deadline effectively.

2. Determine Budget

What is the budget of your project? You probably have a rough estimation regarding your project budget. Nevertheless, you’ll get different offers — depending on where you’re looking. It would help if you also chose a payment model (hourly,  monthly, fixed etc.).

3. Choose Communication Channel

To make all working processes transparent, establish what project management & communication programs and tools you will use with the data engineers. Here are some potential tools that you may require.

These tools will allow you to manage your remote development team, reaching maximum results efficiently:

  • Project Management and Organizing Tools: Jira, Asana, Trello;
  • Repository Hosting Services: GitHub, GitLab, Bitbucket;
  • Messengers That Support Video and Screen-sharing: Zoom, Slack, Discord, and Google Meet;
  • Document Management Software: Google Docs, SharePoint, Confluence.

4. Choose the Platform To Hire a Data Engineering Company

First, you must choose the right platform for hiring a data engineering company. Most startups hire through sites like LinkedIn or Upwork, which offer tools for a quick hiring process. Also, you can consider platforms like Clutch and Goodfirms that provide a list of agencies with experienced data engineers on board.

5. Analyze Cases

Potential vendors’ case studies can help determine whether a company has experience in data engineering for your industry or business domain and how they solve development challenges.

6. Check Reviews

You should check various online platforms that offer testimonials and ratings of data engineering agencies. These websites evaluate the quality of companies based on reviews from verified clients. 

Here are the most famous:

  • Clutch.com — the Clutch team checks the validity of the feedback by independently contacting the writers of the reviews.
  • GoodFirms.co — the evaluation is based on the company’s portfolio and client feedback. 

Skills To Look For In Data Engineer

1. Programming Languages

Like data analysts and scientists, data engineers must have strong programming experience. The most famous programming languages are Java, Python, and SQL/NoSQL:

Java programming language

Most tools and solutions for big data are written in Java. Also, Java allows the building of real-time data streaming platforms to complete challenging computational tasks and automatically visualize insights.

Here are some tips on how to hire an outsourced Java development company.

Python Programming Language

Python is a universal coding language that contains high-level data structures. This language can use data engineers to write Extract, Transform, Load (ETL) scripts and create data pipelines. In addition, Python is used for multiple artificial intelligence (AI) and machine learning applications.


The ideal data engineering team should have experience with SQL and NoSQL databases. SQL is a -specific language for organizing data in relational database management systems, while NoSQL is a non-relational way to manage data. NoSQL databases can store and recover data in any format if the method isn’t relational.

2. Data Warehouses and Data Lakes

Experienced Data Engineers create comprehensive solutions for managing data as smoothly and effectively as possible. Their primary responsibility is to manage the volume, speed and type of enormous data sets from new and unstructured sources. After extracting data from different sources, your hired data engineers must move and store the information in a data warehouse or lake. Data warehouses store structured data, while data lakes work with any kind of information, including streaming and unstructured data.

Your data engineering team should also have knowledge of how to:

  • Establish a cloud-based data warehouse;
  • Combine different data types in data warehouses and lakes;
  • Optimize data warehouse and lake connections for efficiency and effectiveness.

3. Strong Data Expertise

Designed ETL solutions enable you to extract, collect, transform, and consolidate data in an automated way. As a result, you can take all-important management decisions more quickly than your competitors. So, a well-designed ETL system delivers data ready to optimize costs and find growth opportunities.

Learn more about “What Is ETL and How Does It Work?”

Hired Data Engineers should have experience in building ETL (data extract, transform, and load), storage and analytical BI tools. So experience with ETL and BI solutions is critical. Also, data engineers have to store the information in data warehouses or lakes and use BI platforms to connect data sources, such as data lakes, warehouses, and web applications. Engineers should also have enough BI experience to help data scientists build real-time data streaming platforms and dashboards for showing business insights. Tableau, PowerBI, and Google Data Studio are the most popular visualization tools.

4. Cloud Computing

One of the critical skills of the data engineering team is setting up the cloud to store data. It becomes an essential skill to use while working with big data. Businesses work with combination, public or in-house cloud infrastructure based on the data storage needs. Some popular cloud platforms are AWS, Azure, and Google Cloud Platforms (GCP).

Additional Skills That Would Be an Advantage

1. Focus on details: any experienced data engineer should also focus on detail. They also should be able to filter high-quality information from low-quality information and identify areas for improvement and expansion.

2. Problem-solving: data engineers need to be powerful problem solvers to cope with the day-to-day demands of the role. 

3. Communication skills: data engineers need to communicate effectively with people who don’t have the exact level of technical experience or understanding.

The Benefits to Hire Broscorp`s Data Engineers

We help companies to build wholly automated data pipelines starting from collecting survey responses, data analysis, aggregation and serving comprehensive reports to clients. We develop complex web applications, data analytics, sophisticated big-data solutions, and third-party integrations.

Why your next data engineering team should be Broscorp?

There are reasons such as:

1. Business-oriented approach – we don’t just “write code.” We solve real-world challenges with big data.

2. Fast market approach. No more long-running projects that cannot release on time and waste money.

3. Comprehensive technical solutions from ETL to Real-time massive data processing.

In House Development Vs Outsourcing – How To Decide? Check the Pros And Cons Of Each


Big data is changing how we do business, creating a need for top data professionals. So, data engineers help us manage those large quantities of information and value from data. Unfortunately, outstanding Data Engineers are difficult to find. Many brilliant talents have already been hired to work at big companies, creating a vacuum of skill in the job market.  Finding the right person for the job can be difficult if you’re hiring remotely, but it’s not impossible. With our custom data processing services, you can spare yourself from the hassle and find a team that’s dedicated to your needs!

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