Data Engineer Salary in Jersey City, NJ

In Jersey City, NJ, a data engineer can expect to earn a competitive salary. The average yearly salary for this role is around $140,043. This figure reflects a strong demand for skilled data engineers in the area. Companies recognize the value that these professionals bring to their data management and analysis efforts.

The salary range for data engineers in Jersey City varies. Many professionals earn between $108,686 and $158,559 per year. This range shows that experience and skill level can significantly impact earnings. Some top earners in the field make over $208,000 annually. This high earning potential makes data engineering an attractive career choice for many job seekers.

1. Hoboken, NJ
   Average Salary: $164,277
   In Hoboken, you can find many tech companies looking for skilled data professionals. The city offers a vibrant work environment with plenty of opportunities to grow. Companies like Goldman Sachs and Liberty Mutual are hiring.
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2. Weehawken, NJ
   Average Salary: $142,071
   Weehawken is a great place for data experts. The city has a strong tech scene with many companies needing data talent. Working here means you'll be part of a dynamic team. Companies like Hudson Technologies are hiring.
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3. Newark, NJ
   Average Salary: $129,875
   Newark offers a mix of tech and traditional industries. This city is a hub for data jobs, with many companies looking for data professionals. Working in Newark means you'll be in a growing tech environment. Companies like Prudential and Verizon are hiring.
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4. Brooklyn, NY
   Average Salary: $114,636
   Brooklyn is known for its vibrant tech scene. Many startups and established companies are looking for data experts. Working here means you'll be part of a creative and innovative environment. Companies like Etsy and Rent the Runway are hiring.
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5. Manhattan, NY
   Average Salary: $96,553
   Manhattan is a top choice for data professionals. The city offers many opportunities in finance, tech, and media. Working in Manhattan means you'll be in a fast-paced and dynamic environment. Companies like Goldman Sachs and JPMorgan Chase are hiring.
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1. Tradeweb
   Average Salary: $193,750
   Tradeweb offers exciting Data Engineer roles in Jersey City, NJ. They focus on building and managing data infrastructure. Tradeweb operates globally, with major offices in New York, London, and Singapore.
   

   
   

2. Citi
   Average Salary: $182,583
   Citi provides top-notch Data Engineer positions in Jersey City, NJ. They work on large-scale data projects to support financial services. Citi has a strong presence in the U.S., Europe, and Asia.
   

   
   

3. Chubb Insurance
   Average Salary: $171,700
   Chubb Insurance offers rewarding Data Engineer jobs in Jersey City, NJ. They handle data analytics to improve insurance services. Chubb operates worldwide, with key offices in the U.S., Europe, and Asia.
   

   
   

4. Combined Insurance
   Average Salary: $170,000
   Combined Insurance provides competitive Data Engineer salaries in Jersey City, NJ. They focus on data management and analysis. Combined Insurance has offices across the U.S.
   

   
   

5. JPMorgan Chase & Co
   Average Salary: $140,691
   JPMorgan Chase & Co offers attractive Data Engineer positions in Jersey City, NJ. They work on data systems to support banking services. JPMorgan Chase has a global presence, with major offices in New York, London, and Hong Kong.
   

   
   

6. Bank of America
   Average Salary: $131,250
   Bank of America provides good Data Engineer roles in Jersey City, NJ. They focus on data infrastructure and analytics. Bank of America operates globally, with key offices in the U.S., Europe, and Asia.
   

   
   

7. Verisk
   Average Salary: $122,330
   Verisk offers solid Data Engineer jobs in Jersey City, NJ. They work on data solutions to support risk management. Verisk has a global presence, with major offices in the U.S., Europe, and Asia.
   

1. Clinical Data Management Director
   Average Salary: $231,322
   This role oversees clinical data management teams. They work with healthcare companies to ensure data accuracy. They manage projects and staff to meet regulatory standards.
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2. Clinical Programmer
   Average Salary: $203,500
   Clinical programmers create and maintain software for clinical trials. They work closely with data management teams. They ensure data collection tools are accurate and efficient.
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3. Machine Learning Engineer
   Average Salary: $161,549
   These professionals build and deploy machine learning models. They work with tech firms to improve data analysis. They develop algorithms to make predictions and automate tasks.
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4. Software Engineer
   Average Salary: $157,955
   Software engineers develop applications and systems. They work in tech companies to create software solutions. They write clean, efficient code to meet user needs.
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5. DevOps Engineer
   Average Salary: $147,820
   DevOps engineers bridge development and operations. They work with tech firms to automate processes. They ensure smooth software deployment and maintenance.
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6. Market Intelligence Analyst
   Average Salary: $144,788
   These analysts gather and interpret market data. They work for consulting firms to provide insights. They help companies make informed business decisions.
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7. Data Scientist
   Average Salary: $142,787
   Data scientists analyze complex data sets. They work with tech companies to uncover trends. They use statistical methods to inform business strategies.
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8. Quantitative Analyst
   Average Salary: $137,025
   Quantitative analysts use math to solve financial problems. They work for investment firms to model market trends. They develop algorithms to predict market movements.
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9. Clinical Data Associate
   Average Salary: $130,500
   Clinical data associates manage clinical trial data. They work with healthcare companies to ensure data quality. They verify data accuracy and completeness.
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10. Data Modeler
    Average Salary: $127,509
    Data modelers design data structures. They work with tech companies to create efficient databases. They ensure data is organized and accessible for analysis.
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