Hire a dedicated Data Engineer with Lemon.io
Looking to hire dedicated Data Engineer who will be in charge of data processing at your startup. Lemon.io, a marketplace for vetted developer can offer just what you are looking for. Hire with us stress-free!
What is data engineering?
Data engineering is in many ways like building a house. While a house needs a solid foundation to stand on and make it possible for people to live in, working with data requires data engineering to create databases, pipelines, and storage systems to collect and process large amounts of data, thus, making it available and readable for Data Scientists and Data Analysts. This, in its turn, allows them to see meaningful patterns and insights and create predictions for businesses’ future.
In other words, both construction of the house and data engineering require careful planning, ensuring all components are correctly secured so that the base remains stable over time!
What will we cover?
Spent months recruting on other platforms with no results? We understand your frustration. And hey, you are on the right track. At Lemon.io we got skilled devs from around the world. We will definitely find a Data Engineer who fits your requirements and deadlines. Keep on reading to find out more!
What is the role of a Data Engineer?
Getting into more detail, data engineering is the process of preparing, structuring, and organizing data for analysis. Data Engineer, in its turn, transforms raw and unstructured data into an organized form accessible for visualization, analytics, reporting, or machine learning applications.
Data Engineer works to acquire data. Their role is to create data storage and then convert available data into readable format. Among other responsibilities of a Data Engineer is cleaning data from any errors and bugs while also eliminating duplicates and redundancy.
If put into a bulleted list, the daily responsibilities of an average Data Engineer will look like this:
- Data delivery optimization;
- Organization and evaluation of large volumes of data;
- Identification and implementation of infrastructure for scalability;
- Identifying and implementing re-designs of infrastructure for scalability;
- Development of analytical tools for data pipeline;
- Insights derivation for the increase of operational efficiency;
- Development of a platform or framework for data generation, extraction, and loading.
When do you need to hire a Data Engineer?
Ask yourself this question: “Am I in need of building, maintaining, and improving data infrastructure at my startup?” If the answer is “Yes!”- you are on the right track of looking to hire a Data Engineer.
Businesses, these days, rely on technology to help make profitable decisions. While technology can make predictions in seconds, for a human, it might take months to analyze and organize that amount of data. To do it quickly, the technology requires complex systems that can efficiently store large amounts of structured or unstructured information. This is when a Data Engineer comes in handy. They are responsible for designing such architectures so that your business can have access to timely and accurate insights from your data sources.
Why do you need to hire a Data Engineer?
Are your business and team growing? Are your Data Scientists and Data Analysts unable to handle larger amounts of new data and turn it into meaningful insights? Time to hire a Data Engineer who will be working on assembling large volumes of information into a readable format so that your 
Data Scientists and Data Analysts can create market and customer predictions to improve the performance of your business.
How does a Data Engineering expert manage to do it? They do it by:
- Writing code for ETL (Extract-Transform-Lload) pipeline;
- Integrating open source technologies with enterprise databases;
- Managing cloud allocation;
- Optimizing query performance across multiple databases;
- Creating dashboards for reporting purposes.
If neither of your present employees can perform these tasks, then hiring Data Engineer will help your business move onto the next level.
Why is data engineering critical for business?
What use is there of the information in the book if you can’t read it? The same goes for your startup’s data. Therefore, data engineering is the same foundation mentioned above that needs to be put into place to enable machine learning and advanced analytics for businesses to thrive.
As time passes and the world becomes more data-driven, data engineering becomes essential to almost every business. And one cannot exist without Data Engineer who possesses a unique skill set to prepare data for future assessment.
What are the Data Engineer skills?
- Experience with ETL tools;
- Advanced programming knowledge (SQL, Python)
- Knowledge of Cloud computing;
- Experience with data architecture and pipelining;
- Working knowledge of Hadoop;
- Hands-on experience creating data warehouses and data lakes;
- APIs;
- Attention to detail;
- Great communication and teamwork skills;
- Problem-solving mindset.
How do you hire a dedicated Data Engineer?
There are three ways you can do it: bidding platform, direct recruitment, and platforms for vetted developers. What’s the difference, you ask?
Bidding platforms are places to make job posts and place your bid. Data Engineers who think they are suitable candidates will apply. Then you review their applications, contact the most suitable candidates, and set up interviews with them. Although to warn you, this can take up to six months, just like recruiting directly to your company can. While the talent pool is much wider than hiring an in-house employee from your town or country, it might take some time through trial and error to find the suitable Data Engineer according to your needs and requirements here.
Direct recruitment to your company takes a lot of time and resources. By choosing this way, you place responsibility on your recruitment team to be in charge of the process. They will draft and post a job description on job boards and career pages. Data Engineers who are eager to fill in the position at your company will send you their resumes. Afterward, your team will review all the applicants and choose the best candidates. The interview follows next. The chosen candidate will then be assigned a test task. If completed on time and accordingly, you can proceed to drafting an offer and signing a contract. Fewww! It will take time, won’t it?
Finally, platforms for vetted developers, like Lemon.io. What’s so special about them? Well, they cut time, not just by half, but literally by 80 percent. How? This kind of platform has a vetting procedure in place, and by the time you reach them, they have already conducted all the steps before “signing the contract” one. The only couple of things left to you is: to apply, have an interview, sign the contract, and begin working with the perfectly suitable Data Engineer. Why waste time and energy when there are platforms that can help you?
Why should you hire qualified Data Engineers with Lemon.io?
Lemon.io is a marketplace of vetted developers. With us, you can hire the best Data Engineers out there, and we ensure it. How?
- Vetting procedure. Thats how it works at Lemon.io;
- Workflow agility. To boost functionality and productivity, our startup uses an interactive method, such as the Jira application and other technologies, to divide huge projects into smaller tasks;
- Quick matching. Within 48 hours after your request, we guarantee you the first candidate who matches your needs, budget, and time zone;
- Great deals. We have developers at prices that won’t break the bank, but it doesn’t mean they are less skilled than expensive programmers. For instance, a strong middle Data Engineer through Lemon.io will cost you 40 to 45 USD per hour, whilst a senior-level Data Engineering expert will be available at 55 to 60 USD an hour. If you are looking to hire the best Data Engineer of CTO or Tech Lead-level at Lemon.io, you will find them for around 75 USD per hour.
- No red tape. Lemon.io knows how eager you are to begin working with your new Data Engineer who can make your dreams come true. We won’t keep you from that by making you sign tens of papers, unless decided otherwise.
- NDA. As soon as the payment is complete, you become the only owner of the code;
- Prompt reports. You have access to an application through Lemon.io where developers will give you a weekly report on the jobs they completed and how long they took;
- Big talent pool. In our database, we have top Data Engineers from around the world: Latin America, Central, and Eastern Europe, etc. This means that even if you are 11 hours behind us, you will certainly be matched with a Data Engineer that meets your requirements;
- Understanding of remote recruitment. In addition to providing remote developers, the entire staff of Lemon.io also works remotely. As a result, we are quite knowledgeable about our product’s drawbacks. But do not fret! We know our way with it.
- Flexible hiring. Looking for a full-time or part-time Data Engineer to join your team? We can match with either of the candidates.
How do we work with you to find a suitable Data Engineer?
Our relationship begins with your application. You fill in the form on our website, and after careful consideration and revision, our Sales Team gets back to you through an email to set up an interview. This step takes from less than a day to two days.
They collect information about your startup or project requirements, needs, and deadlines throughout the interview. An interview can take between 25 to 45 minutes.
Once both sides are willing to proceed, our Matching Team starts their part.
The Matching Team of Lemon.io is in charge of finding suitable Data Engineers according to your request. This step takes a few hours to a couple of days, and once again, you are being reached to set up a call.
Our Matching Team has found you a suitable Data Engineer or two or three. Now it’s time for you to meet them. These interviews can take between 15 to 60 minutes. At this stage, both sides are welcome to decide on collaboration.
And if the answer is favorable on both ends, Lemon.io Customer Success Team prepares a contract and NDA for signature.
Payment is confirmed, and you can proceed to work with your dream Data Engineer.
FAQ
When should I add a Data Engineer to my team?
Consider hiring a data engineer when:
– you are planning on building build data pipelines, improving the performance of analytics systems, or implementing complex architectures for storing and querying large amounts of data.
– when you are reaching over 50 users on your BI platform;
– you have 3 data scientists or analysts on your team;
– when one of your warehouse tables rolls over 1 billion rows;
Remember, data engineers optimize the work of data scientists and analysts, not do it for them. Their main task remains to make huge volumes of data as readable and useful as possible so that analysts and scientists can derive valuable insights from it later on.
What does a data engineer do day-to-day?
Data Engineer’s daily responsibilities are:
- Data delivery optimization;
- Organization and evaluation of large volumes of data;
- Identification and implementation of infrastructure for scalability;
- Identifying and implementing re-designs of infrastructure for scalability;
- Development of analytical tools for data pipeline;
- Insights derivation for the increase of operational efficiency;
- Development of a platform or a framework for data generation, extraction, and loading.
What distinguishes a great Data Engineer from a good one?
A great Data Engineer understands business needs and creates solutions that don’t overcomplicate the issues. Sometimes, when there is no clear understanding of the startup needs, a Data Engineer might develop a complex solution to the needs that require much less. For instance, building a pipeline that is nearly time-streaming when only daily updates are required.
Lastly, a great Data Engineer has to be a Team player and know how to perform well in a collaborative environment.
What does a Data engineer do?
A data engineer is responsible for extracting and organizing large volumes of data to make them readable for Data Scientists and Data Analysts.
Is data engineering just ETL?
No, the responsibilities of a Data Engineer go further than just working with ETL tools.
How much is a Data Engineer paid?
According to Glasdoor, the median anual salary of a Data Engineer in New York sets at 117k USD, whilst if you take a look at San Francisco, there, the salary of the same Data Enginner increases, establishing the average yearly income at 130k USD.
Have more questions?
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