BI/Data Engineers

Hire BI/Data Engineers

Corporations often possess a vast array of raw data, comprised of marketing figures, human resource information, budgets and sales volumes. While business owners may be cognizant of this data, its value may not be immediately evident until it is mined, processed and presented in a digestible format. To this end, Business Intelligence (BI) is an amalgamation of tools and processes that allows organisations to extract the most from their data, uncovering insights and developing strategies to enhance operations and profitability.

In today’s digital era, organisations are increasingly relying on multiple applications to generate data. This includes enterprise resource planning (ERP), customer relationship management (CRM), production systems, and a multitude of other databases that contain various kinds of information. As the organisation grows, the number of applications and sources of data also increases, resulting in a vast quantity of data scattered across the organisation in different formats. This can make it challenging to identify and visualise the right business environment. To assist with this, data engineers are employed to extract pertinent information from raw data.

As the need for data has grown across the board, the need for BI and data engineer roles has surged. Here’s how to get started as a BI/Data engineer.

What does BI/Data engineering entail?

Business intelligence is an essential tool for data collection, as it involves asking questions, generating reports, and responding to inquiries about past events. Unfortunately, many entrepreneurs fail to recognise the value of business intelligence, mistakenly believing that business analytics alone can provide answers to all of their questions. However, business intelligence is a vital part of data collection, and can often provide solutions to problems that were previously unsolvable.

The demand for positions related to data has significantly increased in recent years, and this upward trend is projected to persist as more companies embrace Big Data. Data engineers are essential in data analysis, taking raw data and transforming it into valuable insights for businesses.

Due to their expertise in analysing complex datasets and extracting pertinent information, Business Intelligence/Data Engineers are held to stringent standards and receive substantial remuneration for their efforts.

What are the duties and functions of a BI/Data engineer?

Data Engineers are responsible for constructing a robust infrastructure for transforming data into user-friendly formats that can easily be interpreted by Data Scientists. They must be able to identify patterns in large datasets and establish scalable procedures to convert unstructured and semi-structured data into useful formats. In other words, they are responsible for preparing and converting raw data for analytical or operational purposes. Business Intelligence (BI) Developers, on the other hand, must collaborate with end users to design and develop reporting systems that provide clear and easy-to-understand data for decision-making. Furthermore, BI Developers must employ business intelligence to address organisational challenges by analysing warehouse data. A typical BI/Data Engineer’s day-to-day work consists of tasks such as data design, access, use, security, and the quality assurance of information assets across the enterprise.

• Work on the design, development, and implementation of data structures for BI systems.
• Make recommendations to improve the performance, data handling, and development process efficiency of the client’s existing BI model.
• In charge of integrating new data quality components into the client’s platform.
• Create and manage comprehensive dimensional data models and multidimensional databases.
• Assist with data extraction from the source system and entry into the data warehouse staging area.
• Validate data, assure data accuracy, and ensure that data is according to business standards.
• Maintain a record of ongoing maintenance and operations for future use.
• Create, restructure, and maintain web services that consume stored data.

How do I become a BI/Data engineer?

Having the correct combination of abilities and skills can be a great start or help advance your career in Business Intelligence/Data Engineering. Generally, acquiring a Bachelor’s degree in Computer Science, or a related field is often a must to work in this industry. As this is an ever-evolving field, a degree can provide you with a solid basis of knowledge. Additionally, obtaining a Master’s degree can help you grow in your profession and open the door to higher-paying positions.

Obtaining a Bachelor’s Degree in Computer Science, Engineering, Applied Mathematics, or a related IT subject is often a necessity for those aspiring to become a BI/Data Engineer. Because the position requires a high level of technical knowledge, prospective BI/Data Engineers may find that a boot camp or accreditation alone will not be sufficient to make them competitive in the job market.

Connecting with other professionals in the Business Intelligence/Data Engineering and Analytics fields can help you gain a better understanding of the job requirements and the skills necessary for success. Establishing relationships with people in the same industry can also provide you with valuable references for potential job opportunities. Additionally, engaging with colleagues at your current workplace or attending networking events are great ways to expand your professional network.

Let’s take a look at the abilities and methodologies you’ll need to master to be a good BI/Data engineer:

Qualifications for becoming a BI/Data engineer

The first stage is to gain the core skills required to get a high-paying position as a BI/Data engineer. Let’s go through what you should know.

1. Business Intelligence platform

   Businesses rely on business intelligence software to collect data from both internal and external sources. During an interview, you should prepare to be asked to evaluate the company’s chosen platform, which can be Oracle, Microsoft, Tableau, or MicroStrategy. Having a well-rounded understanding of the platform’s features, as well as any newly implemented components in the latest version, is essential. Additionally, you should be knowledgeable in the technological architecture of the platform and its competitive advantages compared to other business intelligence software solutions in the market.

2. Apache Hadoop and Spark

   Due to the fact that HTML and CSS are generally static in nature, they are the perfect choice for a website that requires only text. JavaScript is yet another useful feature for developing responsive webpages that can be incorporated. It allows users to add interactive elements to the site, such as polls, slideshows, and forms that can recognise touch commands. This client-side scripting language also enables dynamic elements to be added to the website, like page animation, scrolling, audio, and video.

3. C++

   C++ is highly regarded for its efficiency in processing and analysing large data sets. This programming language is capable of computing data at a rate of one gigabit per second, allowing for real-time predictive analytics and ensuring the security of the main system. Its speed and power make it an invaluable tool for businesses and organisations dealing with large amounts of data.

4. Data modelling

   As a Business Intelligence Developer, it is essential to configure the environment on the BI Platform for accurate reporting and data analysis. To gain an understanding of corporate operations and how data traverses the company, it is necessary to communicate with colleagues. Additionally, strong SQL skills are required to modify and acquire data. Finally, comprehension of the organisation’s BI Platform is essential in order to construct the environment to meet its distinct capabilities.

5. Azure

   Microsoft Azure is a cloud computing platform that simplifies the deployment, administration, and maintenance of servers and applications. This comprehensive solution provides users with the ability to quickly and easily deploy and maintain their servers and applications, as well as access pre-built services for data storage and advanced machine learning. It is essential for BI/Data engineers to have specialised knowledge and expertise in Azure in order to make the most of this platform.

6. APIs for data

   An Application Programming Interface (API) is a tool that allows different software components to interact with each other in order to complete a task. For instance, web applications rely on an API to facilitate communication between the user interface and the back-end functionality and data. This allows the application to access the database, retrieve information from corresponding database tables, process the request, and return an HTTP-based response to the web template, which is then displayed in the web browser. Moreover, data engineers integrate APIs in databases to allow data scientists and business intelligence analysts to query the data.

How can I find remote BI/Data engineer jobs?

It is essential to develop a well-thought-out job search plan in order to maximise your chances of success. Prior to initiating your search, take the time to consider what type of job you are looking for and how you can use that information to narrow down your options. Demonstrating to potential employers that you possess the necessary qualifications and skills to excel in the position is all about gaining practical experience. Therefore, it is essential to continually strive to learn and refine your abilities. Working on open-source, volunteer, and freelance projects can be incredibly beneficial when it comes to having something to discuss in an interview.

At Works, we provide the opportunity to explore the latest technologies and tackle complex technical and business challenges with our selection of the most advantageous remote BI/Data engineer positions. Our network of top-tier developers makes it easy to find full-time, long-term roles that offer a competitive salary and significant growth potential. We understand the importance of providing our candidates with job opportunities that align with their career goals, and that’s why our remote BI/Data engineer positions are the best in the industry.

Job Description

Responsibilities at work

• Assist with the design, development, and implementation of BI platform data architecture.
• We will conduct a thorough review of the client’s existing Business Intelligence (BI) model to assess its performance and data management capabilities. Upon completion of the review, we will provide recommendations to improve the model and make the development process more efficient.
• Lead the development of new data quality components for the client’s platform.
• Create and maintain precise dimensional data models as well as multi-dimensional databases.
• Assist in the extraction of data from the source system into the staging area of the data warehouse.
• Ensure data validation, correctness, data type conversion, and implementation of business rules.
• Make documentation of ongoing repairs and operations for future use.
• Create, restructure, and maintain a web service that consumes stored data.

Requirements

• A bachelor’s or master’s degree in engineering, computer science, mathematics, or statistics is required (or equivalent experience)
• At least three years of hands-on experience as a data engineer is required (rare exceptions for highly skilled developers)
• Excellent SQL and Python knowledge and skills
• Experience with Microsoft SQL Server, SSIS, SSAS, SSRS, and PPS, including understanding of client systems
• Expertise in creating and calling web service APIs
• Knowledge with Microsoft Visual Studio and Team Foundation Server
• Expertise in data collection and analysis
• Experian, Trillium, Informatica, and other data quality solutions must be integrated.
• Working knowledge of multidimensional (OLAP) databases
• Clear understanding of database administration ideas, principles, and data management
• Worked with ETL tools for data extraction, cleaning, optimisation, and loading
• English fluency is required for good communication.
• Work full-time (40 hours per week) with a 4-hour overlap with US time zones

Preferred skills

• Understanding of data lakes and cloud data warehouse platforms
• Working knowledge of Amazon Web Services
• Working knowledge of Agile environments
• Outstanding organisational and interpersonal abilities