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Table of contents
Who is a Data Engineer?
Salary and Perks
Skills Required
Preparation Strategy
Career Path of a Data Engineer
Junior Data Engineer
Mid-Level Data Engineer
Senior Data Engineer
Senior Managerial Roles
How to Apply for a Job Role at Uber?
Resources for Preparation
Interview Resources
Technical Resources
Other Resources
Frequently Asked Questions
What is Uber?
What role does a data engineer play?
What are the various responsibilities of a data engineer at Uber?
What is the eligibility for the data engineer at Uber?
What is the top position in the career map of a data engineer?
Last Updated: Mar 27, 2024

Data Engineer at Uber

Author Aashna Luthra
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Do you want a job as a data engineer at Uber? Great! You are at the right place.

Uber Technologies Inc. (Uber) offers various services- enabling customers to reserve a vehicle and driver to transport them (similarly to a taxi), food delivery via Postmates and Uber Eatspackage delivery, courier services, and freight transportation.


Let us first see who is a data engineer, what roles they perform, and what responsibilities they take care of in general.🏌🏻

Who is a Data Engineer?

Data engineers oversee the design, development, and management of database architecture and data processing systems. The most technical job descriptions in data science are data engineers, who play a vital role in bridging the gap between traditional data science professions and software and application developers.

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Data engineers are responsible for the following:

✔️The process of data collection, analysis, storage, and movement of data, which is the initial step in the conventional data science workflow, is handled by data engineers. 

✔️Monitoring the flow and status of data within the systems.

✔️Data engineers must have advanced knowledge of both SQL and data modeling.

✔️The daily activities of a data engineer mostly revolve around two processes: 

  • ETL (Extract, Transform, Load) procedures, which involve creating tasks for data extraction, transformation, and loading, as well as transporting data between various environments. 
  • Data cleaning procedures ensure that information reaches analysts and data scientists in a standardized and structured state.

✔️They are responsible for establishing and maintaining relational and non-relational databases (such as SQLNoSQL, and PostgreSQL), data warehouses (such as Redshift and Panoply), and big data systems (like Hadoop and Spark).

✔️They are responsible for creating and controlling the data pipelines and programs that move data. 

✔️They collaborate closely with the organization's data scientists and other analytics experts. 

Salary and Perks


Annual Salary Range

₹ 40,50,000 to ₹ 51,80,000

Estimated Annual Salary

₹ 45,00,000

**The salary figures mentioned in the above table are subject to change.


  • Uber provides assistance programs, monthly wellness reimbursements, and complete healthcare.
  • The employees can set aside up to 15% of their qualified income through Uber's employee stock purchase plan.
  • Uber offers significant paid sick days, local holidays, vacation days, and voting days. After every five years of service, each employee is given a four-week vacation.
  • Everyone has access to meals and snacks at Uber workplaces all the time.
  • Uber offers paid parental leave, flexible work schedules, access to Cleo's benefits program, and more.
  • Throughout the month and on special occasions, the employees receive credits for Uber Eats and Rides.

Skills Required

skills required

The following section describes the skills and experience needed to be a data engineer.

✅Database management: Data engineers spend a significant portion of their day working with databases, whether to gather, store, transfer, clean, or consult data. Consequently, data engineers need to be knowledgeable about database management.

✅Programming languages: Coding is necessary for data engineers, just like other data science positions. Data engineers use different programming languages in addition to SQL for various jobs. They should be well-versed in programming languages like PythonJava, and C++. Python works well with essential data engineering tools and frameworks like Apache Airflow and Apache Spark.

✅Communication skills: Data engineers require strong communication abilities to collaborate with people from other departments and comprehend the demands of business executives, data scientists, and analysts. Data engineers may also need to know how to create dashboards, reports, and other visualizations to communicate with stakeholders, depending on the organization.

✅Distributed computing frameworks: A distributed system is a computing environment where different components are dispersed over several computers (sometimes referred to as a cluster) connected to a network. Massive volumes of data processing are the main focus of distributed computing frameworks like Apache Hadoop and Apache Spark, which serve as the building blocks for some of the most amazing big data applications. Any aspiring data engineer must possess some knowledge of one of these frameworks.

Tools and libraries: They should be knowledgeable in analytical tools (such as Power BI and Tableau), machine learning libraries (such as Tensorflow and PyTorch), and other technologies that assist with analytical projects (like ETL tools and big data systems)

✅Stream processing frameworks: Some of the most advanced applications in data science involve real-time data. For data engineers looking to advance their careers, one must understand how to use streaming processing tools like Flink, Kafka Streams, or Spark Streaming.

✅Cloud technology: The market is quickly evolving due to the desire for cloud-based solutions. As a result, a skilled data engineer needs to be knowledgeable about using cloud services and their integration with Big Data initiatives. One should at least be familiar with AWS or Azure

Preparation Strategy

To start preparing to become a data engineer, first, you must fulfill the skills and experience required in the previous section. After acquiring the required skills, knowledge and experience, you should start building projects showcasing your data engineering skills. Once you have built a few projects, share your projects with others on GitHub.

Now comes the next phase, the selection process.

An interview for data engineering is typically divided into technical and non-technical parts. During the technical part, hiring managers will evaluate your technical skills for the position as well as your data engineering skills. Expect questions regarding:

▶️Your resume: Employers are interested in learning about your data engineering-related experiences. For recruiters to evaluate your technical, problem-solving, communication, and project management skills, make sure to highlight in your resume any previous data science positions and projects you have worked on. Additionally, be prepared to provide full details about these projects.

▶️Programming skills: Using Python or a data framework like Spark, you will be required to solve an issue in a short amount of time and with a few lines of code.

▶️SQL: In addition to the programming test, you can also be required to use SQL to solve a problem. Writing effective queries to perform data processing in databases is typically the exercise.

▶️System Design: System design is the technical interview's most complex and likely most challenging section. Data engineers' most important jobs include designing data architectures. You will be required to build a complete data solution in this section, which typically consists of three components: data storage, data processing, and data modelling.

Your potential team members will conduct a personal interview with you after you have finished the technical part of the data engineering interview.

Career Path of a Data Engineer

career path

Junior Data Engineer

Junior data engineers generally take on little jobs supporting and maintaining existing systems when they begin their careers. This could involve anything from testing systems to finding and correcting flaws to enhancing an existing system with new features. The most crucial aspect of a junior data engineer's early years is learning and acquiring practical experience with the technologies they will use in the future of their careers. Additionally, they are learning how the many teams and departments collaborate to discover answers to problems and inquiries that arise.

Mid-Level Data Engineer

After one to three years, a data engineer can be promoted to the mid-level.

They are typically responsible for developing and designing the systems that support data scientists and other analytical team members. At this point, they might still be under the direction of a senior data engineer.

Senior Data Engineer

When data engineers advance to a senior position, they handle more managerial duties. They mentor and assign work to one or more data engineers who work under them. At this point, the data engineer has mastered the technical facets of their job and can create systems and find solutions with reasonable ease.

Senior Managerial Roles

Data engineers can opt to go into more managerial roles once they have at least six years of experience, such as:

  • Director of data engineering
  • Chief data officer
  • Data engineering manager

These roles require the data engineer to have robust data infrastructure and architecture skills and be highly proficient in the technical skills acquired during lower levels. They also demand the data engineer be able to lead and scale analytical teams. Additionally, they must be able to scope out new projects and specify the procedures for creating high-performance systems.

How to Apply for a Job Role at Uber?

Step 1: Go to the official career site of Uber.

career site


Step 2: Search for the 'data engineer' role in the 'search open roles'. Set location to any city in India.

data engineer role


Step 3: Select the role 'Data Engineer II' role. 

job description

Step 4: Click on the 'Apply Now' button and fill out the application form. 

Must Read Product Based Companies in India.

Resources for Preparation

The following section talks about the resources available for preparation for a data engineer at Uber.

Interview Resources

Here is a list of resources available to help you ace the data engineer interview in a structured manner.

  • Interview Bundle - Uber- complete bundle for you to ace your interview at Uber, including commonly asked interview questions and interview experiences.
  • Interview Puzzles- curated a list of top interview puzzles asked in various companies.
  • Top 150 puzzles - a guided path to top 150 interview puzzles.
  • Interview Questions- a complete top interview questions bundle on different topics.
  • Aptitude Preparation- a complete aptitude preparation guide on different topics.
  • Interview Sessions- a complete guide for you to practice in mock interviews to prepare yourself for the actual interview.
  • Interview preparation- a complete preparation guide for you to ace your interview.

You can start practicing problems asked in Uber interview by checking out most asked Uber interview questions in our Problem Lists section.

Technical Resources

The following resources will help you to enhance your technical knowledge related to data engineering. Choose your tracks and start preparing. 

  • Learn Big Data - to learn about big data and related concepts.
  • Python- start learning python on your path to becoming a data engineer.
  • Basics of Python - a guided path to basics of python.
  • Microsoft Excel- a complete blog for you to study MS-Excel.
  • DBMS- start learning DBMS on your way to becoming a data engineer.
  • DBMS walkway - a guided path to DBMS (database management systems).
  • CN Library- a complete library of topics for you to study your desired subject.

Other Resources

Apart from the interview and technical resources, there are other resources that will help you on your path to becoming a data engineer.

enough resources

Alright! Check the video given below for some more help.

Frequently Asked Questions

What is Uber?

Uber offers various services- enabling customers to reserve a vehicle and driver to transport them (similarly to a taxi), food delivery via Postmates and Uber Eats, package delivery, courier services, and freight transportation.

What role does a data engineer play?

Data engineers oversee the design, development, and management of database architecture and data processing systems.

What are the various responsibilities of a data engineer at Uber?

The process of data collection, analysis, storage, and movement of data, which is the initial step in the conventional data science workflow, is handled by data engineers at Uber.

What is the eligibility for the data engineer at Uber?

The candidate needs to have knowledge of database management systems, programming languages, distributed computing frameworks, tools and libraries, stream processing frameworks and cloud technology.

What is the top position in the career map of a data engineer?

The topmost position can be director of data engineering, chief data officer or data engineering manager with nearly 6+ years of experience.


In this article, we explored various things related to the data engineer at Uber, leaving no stone unturned. We explored the roles and responsibilities, salary and perks, skills and experience required for the role, preparation strategy to become a data engineer at Uber, and career path of a data engineer at Uber.

We believe this article on the data engineer at Uber was helpful. To learn more about Uber, check out our articles on


Check out Uber Interview Experience to learn about their hiring process.

Refer to our guided paths on Coding Ninjas Studio to learn more about DSA, System Design, Competitive Programming, JavaScript etc. Enroll in our courses and refer to the problems available and mock tests. Take a look at the interview bundle and interview experiences for placement preparations.
Happy Learning Ninja! 🥷

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