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Data Engineer With Jobs (NOW HIRING)

Centraprise

Data Engineer with Mongo DB

Jersey City, NJ

$119.50K - $143.50K/yr

Data Engineer with Mongo DB Job Location : Charlotte NC / Jersey City NJ / Plano TX (ONSITE) Job Type : Full-Time Must Have Technical/Functional Skills Primary Skill: Data Engineer Secondary: Mongo ...

Centraprise

Data Engineer with Mongo DB

Jersey City, NJ · On-site

$119.50K - $143.50K/yr

Data Engineer with Mongo DB Job Location : Charlotte NC / Jersey City NJ / Plano TX (ONSITE) Job Type : Full-Time Must Have Technical/Functional Skills Primary Skill: Data Engineer Secondary: Mongo ...

Winaxis

Sr. Data Engineer with GCP

Bentonville, AR · On-site

$60/hr

Job Summary - Data Engineer with GCP - Role: Senior Data Engineer (GCP) - Location: Bentonville, AR or Sunnyvale, CA (Day 1 onsite) - Citizenship: US Citizen only - Experience: 12+ years overall; 4+ ...

MSR Cosmos

Data Engineer with DynamoDB

Miami, FL · On-site

Role: Data Engineer with DynamoDB Location: Miami, FL-Onsite Duration: Long Term DynamoDB experience mandatory Skills * Hands on data engineering experience with proven track record of building ...

Deloitte

Sr Databricks Data Engineer

Arlington, VA · On-site

$120.20K - $165.10K/yr

Share this job: Share: Share Sr Databricks Data Engineer with Facebook Share Sr Databricks Data Engineer with LinkedIn Share Sr Databricks Data Engineer with Twitter Caution against fraudulent job ...

InfoVision, Inc.

Data Engineer with Palantir

Dallas, TX

$113.70K - $136.60K/yr

Strong Experience with programming languages using Python and SQL is must. * Strong Experience with Palantir foundry software is must. * Strong experience in analyzing large data set and resolve ...

VTG

Data Engineer with Security Clearance

Chantilly, VA

$118.30K - $142.10K/yr

Overview We are seeking a skilled Data Engineer with at least 5 years of experience designing, building, and maintaining scalable data pipelines and architectures. The ideal candidate will have ...

United IT

Data Engineer with streaming

San Diego, CA

$121.60K - $146K/yr

Data Engineer Location: MTV/San Diego CA (100% Onsite) * Expertise in Apache Flink or streaming exp ... Experience working with Apache Kafka. * Proven experience with projects in Apache Flink production ...

GRVTY

Data Engineer with Security Clearance

Chantilly, VA · On-site +1

$118.30K - $142.10K/yr

Our engineers work to collect, process, and feed analytic tools, turning data into intelligence in response to immediate mission needs, with direct impact on real world situations. You will see your ...

United IT

Data Engineer with Insurance Domain

Chicago, IL

$118K - $141.80K/yr

Data Engineer with Insurance Domain Location: Chicago, IL-Onsite Experience: 11+ Years Must have skills: ETL, DataStage, SQL and Auto Insurance or P&C background and some testing exp * Minimum 10+ ...

Qode

Data Engineer

Pensacola, FL

$108.20K - $130K/yr

New Jersey / Irving, TX / Tampa, FL We are looking for an experienced Data Engineer with strong expertise in Mem Sql (SingleStore) to join our team supporting Incedo projects. The ideal candidate ...

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How much do data engineer with jobs pay per year?

As of Jun 4, 2026, the average yearly pay for data engineer with in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Data Engineer, and why are they important?

To thrive as a Data Engineer, you need expertise in SQL, data modeling, ETL processes, and strong programming skills in languages like Python or Java, often supported by a degree in computer science or a related field. Familiarity with big data technologies such as Hadoop, Spark, and cloud platforms like AWS or Azure, as well as relevant certifications, is highly valued. Strong problem-solving abilities, attention to detail, and effective communication skills help Data Engineers collaborate with stakeholders and troubleshoot complex issues. These competencies ensure efficient data pipeline development, reliable data infrastructure, and support data-driven decision-making in organizations.

What are some common challenges Data Engineers face when working with large-scale data pipelines, and how can they be addressed?

Data Engineers often encounter challenges such as data quality issues, pipeline bottlenecks, and scalability concerns when managing large-scale data pipelines. Addressing these challenges typically involves implementing robust data validation checks, optimizing ETL processes for efficiency, and leveraging scalable cloud-based solutions like AWS, Azure, or Google Cloud. Additionally, collaborating closely with data analysts, data scientists, and DevOps teams helps ensure smooth data flow and timely resolution of issues. Continuous monitoring, documentation, and automation are also key practices for maintaining reliable and efficient pipelines.

What are Data Engineers?

Data Engineers are professionals who design, build, and maintain the infrastructure and systems needed to collect, store, and analyze large amounts of data. They work with tools and technologies that enable organizations to process data efficiently and ensure its quality, reliability, and accessibility. Data Engineers often collaborate with data scientists, analysts, and other IT professionals to support business intelligence and analytical needs. Their work is crucial for turning raw data into actionable insights.

What is the difference between Data Engineer With vs Data Scientist?

AspectData Engineer WithData Scientist
Required CredentialsBachelor's in CS, Engineering, or related field; certifications like AWS, GCP, or AzureBachelor's or higher in CS, Statistics, or related; often with certifications in data analysis or machine learning
Work EnvironmentBuild and maintain data pipelines, databases, and infrastructureAnalyze data, develop models, and generate insights
Employer & Industry UsageTech companies, finance, healthcare, where data infrastructure is criticalResearch institutions, tech firms, marketing, and analytics-focused companies

While Data Engineers With focus on developing and maintaining data infrastructure, Data Scientists analyze data to derive insights. Both roles often collaborate but serve different functions within data teams.

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Data Engineer With jobs near you
Infographic showing various Data Engineer With job openings in the United States as of May 2026, with employment types broken down into 100% Contract. Highlights an 100% In-person job distribution, with an average salary of $129,716 per year, or $62.4 per hour.
Data Engineer with Mongo DB

Data Engineer with Mongo DB

Centraprise

Jersey City, NJ

$119.50K - $143.50K/yr

Other

Posted 10 days ago

Job description

Job Title : Data Engineer with Mongo DB
Job Location : Charlotte NC / Jersey City NJ / Plano TX (ONSITE)
Job Type : Full-Time
Job Description:
Must Have Technical/Functional Skills
Primary Skill: Data Engineer
Secondary: Mongo DB
Experience: Minimum 10 years
Key Responsibilities:
• MongoDB Database Management:
Designing, implementing, and managing MongoDB database architectures, including schema design, indexing, replication, sharding, and performance optimization for large-scale data.
Data Pipeline Development:
Building and maintaining robust ETL/ELT (Extract, Transform, Load) pipelines for ingesting, transforming, and loading structured and unstructured data from diverse sources into MongoDB and other data platforms.
• Performance Optimization:
Optimizing MongoDB queries, aggregation pipelines, and overall database performance to ensure efficient data processing and retrieval.
• Data Integrity and Security:
Ensuring data integrity, quality, and security by implementing appropriate validation, monitoring, access controls, and encryption measures within MongoDB and related systems.
• Collaboration and Integration:
Working closely with application developers, data scientists, data analysts, and DevOps teams to understand data requirements, integrate MongoDB with other systems and cloud services (e.g., GCP, AWS, Azure), and support data-driven applications.
• Troubleshooting and Monitoring:
Monitoring data pipeline performance, troubleshooting issues, and implementing solutions to ensure data reliability and availability.
• Documentation:
Creating and maintaining documentation for data pipelines, database schemas, and data engineering processes.
Required Skills and Qualifications:
• Strong MongoDB Expertise:
In-depth knowledge of MongoDB's features, including document modeling, aggregation framework, indexing, sharding, and administration.
• Programming Proficiency:
Strong programming skills in languages like Python, Java, or Node.js, particularly with MongoDB drivers and related libraries.
• Data Pipeline Tools:
Experience with data pipeline tools and technologies such as Apache Spark, Airflow, Kafka, or cloud-native data services.
• Cloud Platform Experience:
Familiarity with cloud platforms (e.g., Google Cloud Platform, AWS, Azure) and their data-related services.
• Data Modeling and Design:
Ability to design efficient and scalable data models for NoSQL databases.
• Problem-Solving and Analytical Skills:
Strong aptitude for troubleshooting data-related issues and optimizing data systems.
• Communication and Teamwork:
Excellent communication and collaboration skills to work effectively with cross-functional teams.
Domain Knowledge: Banking and Payments.

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