Data Engineer Job with Visa Sponsorship USA

Hurry and apply for this Data engineer job with a visa and earn up to $128,271 yearly and $55.23 to $84.73 hourly. However, you can also enjoy dental insurance, paid time off benefits and more.

Data Engineer Job

The realm of data engineering is brimming with opportunities, and guess what? Some companies are willing to offer visa sponsorship to talented individuals like you.

Imagine diving into the dynamic world of data, harnessing its power to drive innovation and transform industries. As a data engineer, you hold the key to unlocking insights from vast streams of information, shaping the future with your analytical prowess. But what if you could do all this while fulfilling your dream of working in the United States?

Yes, you heard it right. With the increasing demand for skilled data professionals, many companies are eager to extend visa sponsorship to qualified candidates from around the globe. Let’s go deeper.

Data Engineer Jobs

what is data engineer? It is a jobs that cover a multifaceted role crucial to the modern data-driven landscape. As a data engineer, you’re the architect behind the scenes, designing, constructing, and maintaining the infrastructure that facilitates the collection, storage, and analysis of vast amounts of data.

Your primary responsibility revolves around building and optimizing data pipelines. These pipelines serve as the lifeline of data within an organization, seamlessly transferring information from various sources to storage systems and analytical tools.

Whether it’s structured data from databases, semi-structured data from APIs, or unstructured data from sources like social media, your expertise ensures a smooth flow of information.

But data engineering goes beyond just moving data around. You’re also tasked with ensuring data quality and reliability.

Salary of Data Engineer in the US

People often wonder about the salary of data engineers in the US. According to reports from Indeed, updated as of April 22, 2024, the average annual salary for a data engineer in the United States ranges from $128,271 to $196,800.

Jobs Per hour salary Per day salary Per week salary Per month salary Per year salary
Data Engineer $55.23- $84.73 $570- $875 $2,347- $3,601 $9,082- $13,934 $128,271- $196,800


Furthermore, the salary depends on location, experience, and the specific industry. Highly skilled professionals with significant experience and expertise may earn higher salaries than this range.

Some Top Companies for Data Engineers in the United States

In the United States, several top-tier companies offer exciting opportunities for data engineers with visa sponsorship below list with a link to direct you to the application:

Company Name Type of Job Salary per year Salary per hour Benefits Website to apply from Data Engineer $145,027- $263,000 $62.44 – $132 Flexible schedule, paid time off, 401k matching, etc.
Stefanini IT Solution Data Engineer $161,918- $400,000 $69.72- $200 Flexible schedule, paid time off, 401k matching, etc
DCI Solutions Data Engineer $165,537- $263,000 $71.27- $132 Life insurance, high pay, etc.
Technogen Inc Data Engineer $169,373- $400,000 $72.92- $200 Dental benefits
Meta Data Engineer $177,583- $316,000 $76.46-$158 Excellent health benefits, unlimited PTO
Target Data Engineer $48.87- $92.50 $113,511-$185,000 Employee discount
Emergent Software Data Engineer $55.67-$101 $129,292- $202,000 Work from home, dental benefits, etc.
Liberty Mutual Insurance Data Engineer $56.14-$114 $130,385- $227,000 Insurance


Highest Paying Cities for Data Engineers Near United States

There are different types of cities with high-paying salaries for Data Engineers jobs. However, below are some of the cities to relocate to:

City Name Salary Per Year
San Jose, CA $168,723
San Francisco, CA $158,729
Redmond, WA $146,700
Richmond, VA $139,446
McLean, VA $135,943
Boston, MA $132,126
San Diego, CA $130,536
Chicago, IL $125,839
Irving, TX $118,378


High Paying Similar Data Engineers Jobs

There are some similar data engineer jobs to look out for and below are some of them:

Big Data Engineer

Salary Range:

$110,000 – $160,000 per year, depending on experience and location.

Key Responsibilities:

  • Developing and maintaining big data platforms and solutions.
  • Implementing data ingestion, processing, and storage pipelines.
  • Collaborating with data scientists to deploy machine learning models.
  • Prevalent Industries/Companies: Financial institutions, telecommunications, and online retailers, as well as technology startups focusing on data-intensive applications.

Big Data Engineers specialize in handling large volumes of structured and unstructured data. They design and implement distributed systems using technologies like Hadoop, Spark, and Kafka to process and analyze data at scale.

Senior Data Engineer

Salary Range:

$120,000 – $180,000 per year, depending on experience and location.

Key Responsibilities:

  • Architecting and building data systems that support business objectives.
  • Optimizing data workflows for performance and efficiency.
  • Mentoring junior team members and providing technical leadership.

Senior Data Engineers are experienced professionals responsible for designing, implementing, and maintaining scalable data pipelines and infrastructure. They often work closely with data scientists and analysts to ensure data availability and reliability.

Machine Learning Engineer

Salary Range:

$120,000 – $200,000 per year, depending on experience and location.

Key Responsibilities:

  • Developing data pipelines for model training and evaluation.
  • Integrating machine learning models into existing software systems.
  • Optimizing model performance and scalability.
  • Prevalent Industries/Companies: Technology companies like Microsoft, IBM, and Netflix, as well as healthcare, automotive, and advertising industries.

Machine Learning Engineers leverage data engineering skills to build and deploy machine learning models. They work on data preprocessing, feature engineering, model training, and deployment in production environments.

Cloud Data Engineer

Salary Range:

$110,000 – $170,000 per year, depending on experience and location.

Key Responsibilities:

  • Building and managing cloud-based data lakes and warehouses.
  • Automating data pipelines and infrastructure deployment.
  • Ensuring data security, compliance, and governance in the cloud.
  • Prevalent Industries/Companies: Cloud service providers, SaaS companies, and enterprises across various industries transitioning to cloud-based data solutions.

Cloud Data Engineers specialize in designing and implementing data solutions on cloud platforms such as AWS, Azure, and Google Cloud. They leverage cloud services like S3, Redshift, and BigQuery to build scalable and cost-effective data architectures.

Data Infrastructure Engineer

Salary Range:

$100,000 – $150,000 per year, depending on experience and location.

Key Responsibilities:

  • Designing and optimizing database schemas and data models.
  • Implementing data replication, backup, and disaster recovery strategies.
  • Troubleshooting performance issues and optimizing system scalability.

Data Infrastructure Engineers focus on designing and maintaining the foundational components of data platforms, including databases, data warehouses, and streaming systems. They ensure data reliability, availability, and performance.

Data Architect

Salary Range:

$130,000 – $200,000 per year, depending on experience and location.

Key Responsibilities:

  • Developing data architecture strategies aligned with business goals.
  • Collaborating with stakeholders to define data requirements and priorities.
  • Evaluating and recommending data management tools and technologies.

Data Architects are responsible for designing and overseeing the overall structure and governance of an organization’s data ecosystem. They define data standards, policies, and procedures to ensure data integrity, security, and compliance.

Data Science Engineer

Salary Range:

$120,000 – $180,000 per year, depending on experience and location.

Key Responsibilities:

  • Developing data ingestion and preprocessing pipelines for machine learning.
  • Building APIs and microservices for model deployment and inference.
  • Monitoring model performance and implementing model retraining workflows.

Data Science Engineers bridge the gap between data engineering and data science by building scalable infrastructure for deploying and operationalizing machine learning models. They integrate data pipelines with production systems for real-time analytics and decision-making.

Most Common Benefits For Data Engineers

Some amazing benefits come with the job aside from visa sponsorship and below are some of them so far:

  • 401(k)
  • 401(k) matching
  • AD&D insurance
  • Adoption assistance
  • Commuter assistance
  • Dental insurance
  • Disability insurance
  • Employee assistance program
  • Employee discount
  • Employee stock purchase plan
  • Flexible schedule
  • Flexible spending account
  • Gym membership
  • Health insurance
  • Health savings account
  • Life insurance
  • Opportunities for advancement
  • Paid sick time
  • Paid time off
  • Parental leave
  • Professional development assistance
  • Profit sharing
  • Referral program
  • Relocation assistance
  • Retirement plan
  • Stock options
  • Tuition reimbursement
  • Unlimited paid time off
  • Vision insurance
  • Work from home

What skills help Data Engineers find jobs?

There are some skills you need to have before you can have access to this job, and below are the skills:

  • APIs
  • AWS
  • Agile
  • Apache Hive
  • Azure
  • Big data
  • Cassandra
  • Communication skills
  • Data modeling
  • Data warehouse
  • ETL
  • Full-stack development

Roles and Responsibilities

A data engineer uses data to help a machine perform its duties. While a data scientist helps ask the right questions, a data engineer helps gather and collect the answers in addition to storing and processing them. Below are the duties and responsibilities of a data engineer worker in the USA so far:

  • Handling and logging errors
  • Monitoring the system
  • Building pipelines that can tolerate human fault
  • Knowing what is necessary to scale up
  • Addressing constant integration
  • Knowing how to administer the database
  • Maintaining data cleaning
  • Ensuring a deterministic pipeline


Here are the key requirements for a Data Engineer job with Visa Sponsorship in the USA, presented in bullet points:

  • Bachelor’s degree or higher in Computer Science, Engineering, Mathematics, Statistics, or a related field.
  • Strong proficiency in programming languages such as Python, Java, Scala, or SQL.
  • Experience with big data technologies and frameworks like Hadoop, Spark, Kafka, or Flink.
  • Familiarity with cloud platforms such as AWS, Azure, or Google Cloud, including relevant services like S3, Redshift, BigQuery, or Data Lake.
  • Proficiency in data modeling, ETL (Extract, Transform, Load) processes, and data warehousing concepts.
  • Experience with distributed computing and parallel processing techniques for handling large datasets.
  • Knowledge of database systems such as MySQL, PostgreSQL, MongoDB, or Cassandra.
  • Excellent problem-solving skills and the ability to troubleshoot complex data issues.
  • Strong communication skills and the ability to collaborate effectively with cross-functional teams.
  • Familiarity with Agile methodologies and DevOps practices for continuous integration and deployment.
  • Prior experience working with machine learning models and data science workflows is a plus.
  • Eligibility for visa sponsorship to work in the United States, including H-1B visa sponsorship if applicable.

How to Apply

Here’s a step-by-step guide on how to apply for a Data Engineer job with Visa Sponsorship in the USA:

Research Job Opportunities:

  • Start by researching companies that are known to sponsor visas for international candidates.
  • Look for job openings specifically mentioning visa sponsorship or those open to candidates requiring sponsorship.

Update Your Resume/CV:

  • Tailor your resume to highlight your relevant skills, experience, and qualifications for the Data Engineer position.
  • Emphasize your proficiency in programming languages, experience with data technologies, and any prior work with large datasets.


  • Use professional networking platforms like LinkedIn to connect with recruiters, hiring managers, and professionals working in data engineering roles.
  • Networking can help you learn about job openings and increase your chances of getting referrals.

Apply Online:

  • Visit company career websites, job boards, and online platforms like LinkedIn, com, Glassdoor, and Monster to search for Data Engineer positions with visa sponsorship.
  • Submit your application through the company’s online application portal, ensuring you attach your updated resume/CV and any other required documents.

Write a Compelling Cover Letter:

  • Craft a personalized cover letter expressing your interest in the Data Engineer role and why you’re a suitable candidate. Highlight your relevant skills, experience, and enthusiasm for the opportunity.
  • Clearly mention your need for visa sponsorship in your cover letter to avoid any misunderstandings.

Prepare for Interviews:

  • If your application is shortlisted, be prepared for technical interviews, coding assessments, and behavioral interviews.
  • Practice answering common interview questions related to data engineering, problem-solving, and your past experiences.
  • Familiarize yourself with the company’s products, services, and culture to demonstrate your genuine interest during the interview process.

Discuss Visa Sponsorship:

  • During the interview process, be transparent about your visa status and the need for sponsorship to work in the USA.
  • If the company expresses interest in moving forward with your application, discuss visa sponsorship details with the HR or immigration team.
  • Be prepared to provide any necessary documentation or information required for the visa sponsorship process.

Follow Up:

  • After interviews or discussions about visa sponsorship, send a follow-up email thanking the interviewers for their time and expressing your continued interest in the position.
  • Stay proactive and responsive to any communication from the company regarding the status of your application or visa sponsorship process.

Negotiate Offer and Acceptance:

  • If you receive a job offer, carefully review the terms, including salary, benefits, and visa sponsorship details.
  • If needed, negotiate any aspects of the offer, including relocation assistance or visa-related expenses.
  • Once you’re satisfied with the offer, formally accept the job offer and begin the necessary steps for visa sponsorship and relocation, if applicable.

Prepare for Relocation:

  • If you’re relocating to the USA for the job, start making arrangements for housing, transportation, and other logistics.
  • Ensure you have all necessary documentation and paperwork for the visa application process, and follow any instructions provided by the company’s HR or immigration team.

By following these steps and staying proactive throughout the application process, you can increase your chances of securing a Data Engineer job with visa sponsorship in the USA.

Type of Visa Sponsorship Expecting

For a Data Engineer job in the USA requiring visa sponsorship, the most common type of visa needed would typically be the H-1B visa.

The H-1B visa is a non-immigrant visa that allows U.S. employers to temporarily employ foreign workers in specialty occupations, which often include roles in fields like technology, engineering, and science.

Here’s why the H-1B visa is commonly used for data engineering roles:

  • Specialty Occupation: Data engineering typically requires specialized skills and knowledge in programming, data processing, and database management. These roles often meet the criteria for a “specialty occupation” under H-1B visa regulations.
  • Educational Requirement: The H-1B visa typically requires applicants to have a bachelor’s degree or higher (or its equivalent) in a field related to the specialty occupation. Many data engineers hold degrees in computer science, engineering, mathematics, or related fields, which meet this requirement. Etc.


Is Data Engineer A Coding Job?

Yes, data engineering involves a significant amount of coding. Data Engineers use programming languages such as Python, Java, Scala, SQL, and others to design, build, and maintain data pipelines, data warehouses, and other data infrastructure. Proficiency in coding is essential for tasks such as data ingestion, transformation, processing, and integration.

Is Data Engineer A Well-Paid Job?

Yes, a Data Engineer is generally considered a well-paid job. Data Engineers command competitive salaries due to the high demand for their skills and expertise in designing, building, and maintaining data infrastructure. Salaries for Data Engineers can vary based on factors such as experience, location, industry, and company size, but they often fall within a lucrative range, especially for experienced professionals.

Can I Become A Data Engineer Without Coding?

While it’s technically possible to work in data-related roles without extensive coding skills, proficiency in coding is typically a fundamental requirement for Data Engineer positions. Coding is essential for tasks such as data manipulation, automation of data workflows, optimization of data pipelines, and development of data-driven applications. However, individuals with limited coding experience can start by learning programming languages and gaining practical skills through online courses, tutorials, and hands-on projects to transition into a Data Engineer role.

More Related Content

Previous articleDental Insurance That Cover Braces
Next articleInsurance Broker Jobs