Data Engineers are the civil engineers of the Data World. They play a key role in building reservoirs to store & manage the data that’s used for digital activities. Well, to become a freelance data engineer, it is equivalently important to be aware of its roles and responsibilities. Data Engineers are software & IT professionals who develop, construct, test & maintain the data storing architecture. Mainly, all about the databases, & big data processing systems. They install continuous pipelines that enable the data scientists to retrieve data for their research & analysis.
Where to get Started?
In general, candidates who hold the role of business analysts, & data administrators gain some advanced skills to transform into Data Engineers. But, ya! This opportunity of freelance data engineer is not just for early professionals but also is for freshers who are keenly interested to pursue it. Let’s see how gaining hottest skills can take you to top places.
What are some Key Data Engineering skills?
For building a progressive career in Data Engineering, a solid foundation in coding skills, familiarity with cloud computing skills & database design skills serve as prerequisite.
- Perfect coding skills in evergreen programming languages like Python, Java, Scala & Database skills by mastering SQL & NoSQL databases. NoSQL is also important since many relational database systems can’t keep up the big data. Here, Practice is the Key!
- The in & outs of relational & non-relational databases is a must. Databases come into the picture for fulfilling the data storage needs. Thus, an aspiring candidate needs to be a jack of both relational and non-relational databases, & their working.
- Big data needs variations in the methods of data storage. Designing data solutions & when to use which solution makes you standout among others. Say, for example, you need to be aware when to use data warehouse and when to use a data lake.
- Mild overview on Machine learning will enable the synchronization with the needs of data scientists in your team.
- Handle Data with ETL Process! Data engineers are expected to follow the ETL(extract, transform, & load) process for moving the data from databases as well as other sources into a single repository. Most commonly to a data warehouse. Get your hands dirty with some of most used ETL tools include Stitch, Alooma, Talend & Xplenty.
- Ability to enable automation & do scripting for processing big data in a repetitive mode. Writing scripts to automate tasks is a trademark skillset for a data engineer.
- Collaborate with Data security team – Though many companies hire dedicated data security professionals, many data engineers are expected to securely manage and store the data from manipulation, loss or theft.
- Knowledge of utilizing cloud services from popular providers like AWS, Microsoft Azure, Google Cloud, etc is essential as e-companies heavily implement cloud computing.
- Handle Big data tools like Hadoop, MongoDB, and Kafka since Data engineers are big data managers too. So, being proficient in big data tools and technologies will come in handy.
Where to showcase your career profile & Where to get clients?
Websites like Upwork, Fiverr, Freelancer are available to portray your talent & skills to take up the projects. Many freelancer data engineers have reported an income of 30$/hour where the clients were ready to pay off well for data retrieving, data warehouse, data architect skills, & for preparing insightful dashboards. A whole month’s salary earned by a full-time data engineer in corporate can be equivalently earned by the paycheques offered on freelancing in just a week of a month. Indicating more leisure time & more money in-hand!
Quick tip for grabbing the attention of clients to work on freelance projects
The process is to send proposals to the business clients for their work requirement ads. Many of the freelancers try to exhibit their skillset that aligns with lengthier job descriptions in their proposals. This approach is unproductive one and proves to be a waste of time for both freelance applicants and the clients. Then, what is the solution to attract the clients?
#1 The solution is to focus on the solution!
Yes! Clients wants solutions to their business problems. So, its wise to catch their eye with the readymade solutions that you could offer them. Your proposal needs to be clear & concise with possible solutions which are to the point & relevant to their business problems.
#2 Attach your work samples!
This is an effective selling tool for any freelancer. And, this is true for freelance data engineer too. Firstly, to prove your capability in handling the freelance project, it is best to attach the data architecture diagrams, or dashboards of your previous work. This achieves the credible factor among your prospective clients & will turn out to be favourable situation to assign you the job for their requirements.
A typical full-time Data Engineer earns an average of 8LPA while a skilled freelance data engineer earns around 2-3 lakhs per month itself! Now, are you willing to make huge money within few data engineering projects? Then Game up for Upskilling yourself into a Talented Data Engineer where you could schedule work in your fashion. Need a Full-time role only? That needs relevant skills too! Try ZEN Class – the Virtual BootCamp for Upskilling in Data Engineering by GUVI. This Data Engineering Career Program of ZEN-class offers 100% Placement Support with Industry accredited Certifications. SO…, Full-timer or Freelance Data Engineer, ball is in your court but gain the top-trending data engineering skills to set your position in this high-paying industry.