Data Engineer Jobs

Introduction to Data Engineer Jobs

• By definition, we can elaborate the Data Engineer as a type of software engineer who is dedicated to the data resolutions consisting of technologies to be used and scalability of various solutions. There is a slight difference between a software engineer and a data engineer: the first one operates with data concepts and the latter one is concerned with writing code only for data pipelines.
• The data engineer job is exceptionally related to functioning as a technical professional, who is accountable to design and retain the planning of data systems that integrates perceptions extending from analytic frames to a data warehouse.
• Data Engineer Jobs involves the technicians who are dedicated to developing the steps and processes implemented in modelling, verification, mining, and acquisition.

Top Data Engineer Jobs (USA)

Data Engineers can be said as the human assets who are accountable for operative data engineering practices working in any organization generating data reservoirs and configuring pipelines to transfer sorted data info. It is also a science for assembling and authorizing the information that can be leveraged by data scientists.

After extensive research and analysis, the team of Zippia’s data scientists found that:

• Presently, there are over 7,390 data engineers engaged in the United States.
• Women are 18.8% of total data engineers but men are only 74.0%.
• A working data engineer has a normal age of 39 years.
• The furthermost corporate culture of data engineers is white about 57.1%, further trailed by Asian about 27.7%, and Latino or Hispanic about 7.4%.
• The normal data engineers are positioned in New York, NY, and IL, Chicago.
• They are paid $99,766 of the average annual salary.
• The average beginning salary is about $74,000.
• 92% was earned out of what men earned by women in the year 2021.
• The maximum 10% of uppermost salaried data engineers earn as much as $133,000 or even more.
• 15% of entire data engineers are LGBT.
• They are more expected to work at communal companies in contrast to the reserved companies.

Job Responsibilities

For applying data Engineer jobs, one should have the following key job responsibilities mentioned below:

1. Develop and support the prime architecture of data pipeline.
2. Gather big, composite types of data sets which can satisfy both functional and non-functional business necessities known as Data Acquisition.
3. Recognize, design and execute internal process enhancements: mechanizing manual processes, elevating data distribution, re-designing frame for better scalability & so on.
4. Construct the frame needed for the finest extraction, conversion and loading of records from an extensive range of data sources by means of SQL and AWS ‘big data’ knowledge.
5. Figure out analytics tools that operate the data pipeline for delivering actionable visions into client acquirement, functioning proficiency and other main business enactment metrics.
6. Effort with investors consisting of the Management, Product, Data & Design crews for helping with data associated procedural issues and also supporting their data setup necessities.
7. Hang onto our data disconnected and secure diagonally national limitations over and done with numerous data centre and AWS sections.
8. Make data implements for analytics and data scientist crew members who support them in constructing and enhancing our product into an advanced industry leader.
9. Operate with statistics and analytics specialists for struggling for better functionality in our data schemes.
10. Implement programming language and also tools associated with it.
11. Discover unseen patterns by means of data chunks and developing models.
12. Provide updates to the sponsors on the basis of analytics.
13. Effort in sync with inner & outer crew members such as data scientists, data architects and data analysts for management of all kinds of technical concerns.
14. Assimilation of data controlling processes into the administration’s recent structure.
15. Data safekeeping & authority with present-day safety controls.
16. Data storage using technologies like: NoSQL, Hadoop, Amazon S3, and so on.

Qualifications and Salary

• The qualifications compulsory to become an efficacious Data Engineer can be listed as:
• Achieve your respective undergraduate degree, sooner from universities and begin functioning on related projects.
• Store entry-level professional experience
• Collect trained certifications
• Improve data engineering abilities – programming code, database design, automation, cloud computing, etc.
• Carry on acquiring an upper degree in computer science, engineering, etc.
• Brush up on exploration and computer engineering skills.
• Retain posting your related work on Github, LinkedIn platforms.
• Encompass self-learning by means of online courses.
• Familiarize assignment-centred learning methods.
• For proving your merit as a Data Engineer some certifications can be picked up such as IBM Certified Data Engineer, Google Cloud Certified Professional Data Engineer, CCP Certified Data Engineer, Certificate in CPEE.

Data Engineer should possess few essential technical and soft abilities which can support them accomplish their finest and make administrations control their superlative perspective mentioned as follows:

1. C++
2. Azure
3. Database systems like NoSQL, SQL
4. Distribution system basics: Apache Spark, Apache Hadoop
5. ETL (Extra, Transform, Load) tools
6. Scala
7. Amazon S3/HDFS/AWS
8. Python, Scala, Java languages
9. Machine learning algorithms
10. Data structures, data lakes, data modelling, data architecture
11. Data APIs
12. ELK Stack
13. Software Development
14. Apache Airflow, Apache Kafka
15. Business intelligence and analytics or dashboards.
16. Operating systems(OSs) such as UNIX, Solaris, Linux
17. Visualization/dashboards/big data analytics
18. Business intelligence and analytics
19. Understanding of functioning with connectors – SOAP, REST, HTTP, FTP
20. Team skills with Collaboration
21. Presentation and communication skills

Salary of Data Engineer can be

As per the record of Glassdoor, a data engineer’s average salary is evaluated to be $137, 776 per year, depending on skills with a reported salary range of $110, 000 to $155,000 (in India it’s Rs. 8, 56, 643 LPA). While the senior data engineers can earn up to $172,603 of average salary per year having a reported range of salary $152,000 to $194,000. Few salary details paid on average to the data engineers in some top tech companies can be listed as:

Organization Reported Salary Range Average Annual Salary

The salary usually depends on various elements such as size and status of the company, educational merit, topographical location, career position, and also experience in working. Presumed companies and big performers in the Big Data production like Airbnb, Amazon, Netflix, Spotify, Deloitte, Accenture, IBM, and Capgemini, to label a few, generally pay great reimbursement to data engineers.

Conclusion

• Data engineers require obligating a concrete understanding of universally applied scripting languages and are estimated for supporting the secure development of enhanced Data Quality and improved quantity, with the help of leveraging and refining data analytics systems.
• Today, the demand is probable to grow speedily as many businesses and institutions need a vigorous Data Architecture to save and fetch data. Data Engineers are required when an institute expands into implementing Data Science. Not experience in other jobs but really several data engineer jobs need experience in a title role that is a software engineer.

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