Remote Python/Data engineer jobs

Data engineers need to have a strong command of scripting languages like Python to solve complex problems on a coding level. Python-data engineering jobs responsibilities include building, maintaining data pipelines, warehousing Big Data, etc. are the most insightful information from the raw data.

Remote Python-data engineering jobs are seeing an exponential increase as more and more companies worldwide lean towards data. If you have gained expertise and fine-tuned your data science skills, you can be a top Python-data engineer. Data engineering offers the opportunity to bag a secure, high-paying remote job.

Python-data engineering jobs are not always entry-level roles, but you can shift to managerial positions or become a data architect or machine learning engineer after a few years of experience and vast expertise. Even data engineers may also start their careers as software engineers or BI analysts.

As long as companies accumulate and process huge data sets, data engineering jobs will be in demand. While data engineering jobs are the top trending jobs in the technology industry, LinkedIn further listed Python-data engineering jobs in the list of jobs on the rise in 2021 and in the years to come.

Data engineers play a vital role in an organization’s progress. They create scalable solutions with their Python programming and problem-solving skills.

Typically Python-data engineering jobs responsibilities are focused on developing and maintaining an organization’s data infrastructure that includes databases, data warehouses, and data pipelines. A data engineer primarily needs to transform data into a format that is actionable for analysis.

The data transformation cycle starts with cleaning, organizing, processing raw, and unorganized data. Next comes the data pipelines that refer to the configuration of the data processing and data storage systems. In this cycle, data engineers design and deploy systems to collect raw data from a SaaS platform or email marketing tool, clean, transform, and route data to destination systems, and store it in a data warehouse. Later, these data can be easily analyzed by data scientists using analytics and BI tools.

Though the primary task for data engineers is managing and organizing data, they also need to stay updated with the latest trends or deviations that may strike business goals. Overall, this is an exclusive technical position, which requires extensive knowledge and experience in programming, mathematics, and computer science. And specifically for the Python-data engineering jobs, the engineers need to have an exceptional grasp of the Python programming language.

Data engineers have to collaborate with other members, including data architects, data analysts, and data scientists, to research and discover new data accumulation methods and more efficient utilization for existing data.

Thus, Python-data engineers should be able to perform some common tasks when working with data, like -

• Collecting datasets that align with business requirements
• Developing algorithms to convert data into useful and insightful information
• Building, testing, and sustaining database pipeline architectures
• Collaborating with management to recognize company objectives
• New method development for data validation and data analysis tools
• Ensuring agreement with data management and security policies

Let's move on to the path that one must take to pursue a profession in the Python-data engineering jobs field. To begin, keep in mind, you need to be formally educated with a major in mathematics, statistics, computer science, or any relevant subject to become a data engineer. Other than this, you also need command of the relevant technical and non-technical skills. Fresher data engineers may get jobs in start-ups and smaller businesses where they will work in all the areas of data engineering.

However, you may have heard that to get remote Python-data engineering jobs, you must have 3-5 years of experience. It is true for a couple of reasons.
First, industry experience allows you to recognize the vast opportunities while working remotely in top Silicon Valley companies.
Second, many organizations hire candidates with a proven track record to ensure a risk-free, fruitful hire.

Now, let's look at the skills and practices you'll need to master to join the league of remote data engineers.

The first step is learning the fundamental skills that can get you high-paying remote Python-data engineering jobs. Let’s take a look at what you need to know!

1. Coding

Proficiency in coding with Python programming language is essential to bag Python-data engineering jobs. Besides Python, knowledge in other common programming languages, including Java, R, Scala, SQL, NoSQL, etc., is a plus.

2. Relational and non-relational databases

Knowledge of databases is crucially important as it is one of the most common solutions for data storage. A prospective Python-data engineer should have familiarity with both relational and non-relational databases and their work process.

3. ETL (Extract, Transform, Load) systems

Through the ETL system, data is moved from databases and other sources to a single repository, like a data warehouse. Therefore, the data engineers must master the common ETL tools, such as Xplenty, Stitch, Alooma, and Talend.

4. Automation and scripting

Automation is essential when working with Big Data. As organizations need to collect information from the raw data and perform repetitive tasks, they hire efficient data engineers who write effective scripts to automate these tasks.

5. Big Data tools

Data engineers not only work with regular data, but they are also responsible for managing Big Data. New tools and technologies are emerging and different organizations have different preferences; therefore, the data engineers need to master popular Big Data tools, like Hadoop, MongoDB, and Kafka.

6. Programming languages

Python is the top programming language used for statistical analysis and modeling, whereas Java is used in data architecture frameworks. Scala is an extension of the Java language and is interoperable with Java.

7. Algorithms and data structures

Though the Python-data engineering jobs focus on data filtration and data optimization, basic knowledge of algorithms helps understand the larger scenario of the organization’s overall data function. It also helps in defining checkpoints and end goals for the business problem at hand.

Data engineers need to work hard enough to stay updated with all the recent trends and market aberrations and grow their skills gradually over time. In order to excel at their profession, they have to practice effectively and consistently. In that regard, there are two major factors that engineers must focus on to progress. They might get support from someone who is more experienced and effective in training new techniques while they are practicing. Further, as a data engineer, it's vital to fine-tune your analysis, computer engineering, and big data skills, so make sure there is someone who will help you out and keep an eye on your progress.

Turing offers the best remote Python-data engineering jobs that suit your career trajectories as a Python-data engineer. Grow rapidly by working on challenging technical and business problems on the latest technologies. Join a network of the world's best developers & get full-time, long-term remote Python-data engineering jobs with better compensation and career growth.

At Turing, every data engineer is allowed to set his/her rate. However, Turing will recommend a salary at which we know we can find a fruitful and long-term opportunity for you. Our Python-data engineering jobs recommendations are based on our assessment of market conditions and the demand that we see from our elite customers.