The Big Data Engineer performs tasks related to analyzing and storing large amounts of data. These tasks may involve writing SQL queries, and scripts, or calling APIs. They must be knowledgeable about various data storage and query tools. A Big Data Engineer should also be able to integrate with the rest of the organization’s technical team. They must also support the business team and ensure that the results of their work are relevant to the organization’s success.
A Big Data Engineer can help a company use big data to make better decisions based on the analysis and reporting of data. In addition to data analysis, big Data Engineers must be able to develop tools to help other teams analyze data and determine business outcomes. Generally, a Big Data Engineer has previous work experience, but it is not necessary to be a software engineer to enter the field.
A Big Data Engineer should possess a background in programming, enterprise architecture, data science, and software engineering. In addition, they should have experience in testing patterns and large data infrastructures. As a big data engineer, you can expect a compensation package that is far more than the average salary of a similar position. The average salary of a Big Data Engineer in San Francisco is $130,674, which is 4% more than the national average. On the other hand, a Big Data Engineer in Chicago earns only $68,931 on average.
Who is a big data engineer?
A big data engineer is a highly technical person who is also a software developer. He needs to deal with massive databases to emanate valuable data for analysis. Organizations can use this analysis to assess their performance in existing market scenarios. Thus, this analysis helps them grow.
A big data engineer understands programming languages like Python, R, and various cloud platforms. He gathers data from multiple sources and pre-processes it. He then furnishes it to data analysts and scientists for systematically extracting information and insights.
What is big data?
Big data refers to massive databases. The size of these vast databases usually varies from terabytes to petabytes. The data can be associated with the customers and the products and includes operational data. A good deal of this data comes from e-commerce, social media, and smartphones.
According to research, big data has the potential to see the far side of the present, and it can presage market fluctuations and trends.
What are the big data engineer’s roles and responsibilities?
A big data engineer accumulates and ingests the data into a big data environment. He is responsible for handling scalable ETL techniques, and ETL stands for Extract, transform and load. He creates data pipelines using algorithms to convert them into operational data. The principal big data engineer’s roles and responsibilities are as follows:
- A big data engineer has a prominent role in designing, testing, and maintaining a complex data processing scheme.
- A data engineer is the brains behind data collected from various sources.
- He stores data in suitable places like data repositories and data lakes.
- He is supposed to clean, filter and process the data using different algorithms.
- He resolves the ambiguities in data.
- Furthermore, he provides relevant and actionable data to data analysts and scientists.
What are the big data engineer skills?
A Big data engineer requires problem-solving skills along with other technical skills. He is required to deal with cloud computing environments. He assists in documenting requirements, resolving data ambiguities, and more.
Big data engineering requires the understanding of:
- Database architecture
- All data-related archetypes, coding, algorithms, and object-oriented programming.
- Programming languages (such as Python, C++, etc.)
- Scraping, APIs, relational (such as SQL) and NoSQL databases (such as Hadoop), repositories, etc.
- Collecting data from different sources and abstraction tools (such as Kubernetes).
- Statistical programs, MATLAB and SAS.
- Data transformation tools and techniques.
- Processing of all types of data, such as:
- Structured (i.e., spreadsheets, etc.)
- Semi-structured (i.e., JSON files, etc.)
- Unstructured (i.e., text, video, audio, etc.)
- Machine learning algorithms
- Algorithms for predictive models
- the basics of distributed systems
What is the difference between a data analyst, a data scientist, and a big data engineer?
As we have discussed, big data engineers are responsible for collecting data. They build and maintain the data systems.
A Data Analyst is typically responsible for gathering and interpreting data to solve a particular problem. Data analyst rely on the data systems that big data engineer provides.
On the other hand, Data Scientists deal with cleaned data. The role is similar to data analysts, but data scientists work on a higher level. They create methods to derive valuable insights from data and make predictive models.
What is the big data engineer’s salary in India?
The importance of data has increased the demand for big data engineers in the industry. The big data engineer’s salary depends on the level of education and experiences the person. Compared with their less qualified counterparts, professionals with master’s degrees or higher earn significantly more. Not only on the education but salary also depends on the location.
According to research, the average salary of big data engineers worldwide is 108k US dollars. While, the big data engineer’s salary in India ranges from 4.2 LPA to 22 LPA, with an average of 9.1 Lakhs Per Annum. Data Analysts and Data Scientists earn on average 4.1 Lakhs per annum and 11 Lakhs per annum, respectively.
How can you become a big data engineer?
A big data engineer should have a good data processing base and be willing to learn new tools and technologies. Ideally, a big data engineer has experience in business intelligence, data science, and data warehousing.
The first step of becoming a big data engineer is developing a keen interest in computer science and math. As a big data engineer, you need a minimum of a bachelor’s degree. A Master’s degree or higher is a plus point. Following are some technical areas that can help you grow in this field:
- Data architecture and data modeling.
- Programming languages such as Python, C++, and R programming.
- SQL and NoSQL databases, MATLAB, R statistical programs, and Machine learning algorithms.
- Algorithms for predictive modeling.
- Text analysis and Natural language processing (NLP)
- Power Business Intelligence (BI)
The next crucial step in the journey would be gaining experience. Big data engineers require more than just academic skills, which come with experience. Other essential skills are:
- Communication skills
- Problem-solving skills
- Analytical skills
- Interpersonal and business skills
- Multi-tasking
Certification is optional, but at the same time, it is very influential. You must have pertinent certificates to prove your skills and stand out from competitors. Certification will make your candidature more appealing to prospective employers. To be a successful big data engineer, you might need several certifications; a few of them are as follows:
- Certification in Hadoop
- Certification in MongoDB
- Certification in data analytics
- Certificate in machine learning and AI
Conclusion
In today’s time, we can not neglect the importance of data. A big data engineer can use data to derive valuable insights into market trends, and it can solve most business problems on a bigger scale. A big data engineer is an experienced software developer proficient in dealing with big data. Programming languages like Python, SQL, and cloud platforms are crucial for big data engineers. He is a problem solver and analytical thinker.
Data engineers gather, clean, and process data from various sources using computational algorithms. His next step is providing this data to data analysts and scientists. Then, these downstream consumers use it for further interpretation. Thus, he is the unsung hero of the data economy.
Big data engineering is a job of today’s world. There is a high demand for big data engineers in India and everywhere in the industry. A big data engineer is needed in almost all fields, such as finance, healthcare, science, and government. It comes with reasonable remuneration and perks. It would be best if you had a keen interest in computer science and math and a bachelor’s degree to become one. You can thrive in this field as you gain experience, certification, and qualifications.
