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Data Engineering Jobs (NOW HIRING)

Manager of Data Engineering Location: Toronto/GTA Company Overview: Our client is a premier Data Cloud and Business Intelligence consulting company specializing in helping businesses harness the ...

The Data Engineering Lead plays a critical and strategic role in advancing FMHC's enterprise data transformation and analytics enablement efforts. This role provides technical leadership, direction ...

The Manager, Data Engineering will facilitate the definition of data solutions, technical architecture, and delivery plans while ensuring high standards of data quality, governance, and security.

$140K - $160K/yr

Data - Engineering Employment Type: Full Time Location: 1668 S. Garfield Ave. 2nd Floor, Alhambra, CA 91801 Compensation: $140,000 - $160,000 / year Description We are seeking a highly motivated ...

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Data Engineering information

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$46K

$165K

$243.5K

How much do data engineering jobs pay per year?

As of Jul 7, 2026, the average yearly pay for data engineering in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

Is AI replacing data engineers?

AI is automating certain tasks within data engineering, such as data cleaning and pipeline management, but it does not replace the need for data engineers. Data engineers are essential for designing, building, and maintaining complex data systems, and their expertise in tools like SQL, Spark, and cloud platforms remains critical for managing data workflows and ensuring data quality.

What work does a data engineer do?

A data engineer designs, builds, and maintains data pipelines and infrastructure to collect, store, and process large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible, reliable, and optimized for analysis by data scientists and analysts.

What are the typical daily responsibilities of a Data Engineer?

Data Engineers regularly design, build, and maintain scalable data pipelines to support analytics and business intelligence teams. Their daily tasks often involve working with large datasets, optimizing data storage, ensuring data integrity, and troubleshooting data-related issues. Collaboration with data scientists, analysts, and software engineers is common to align on data requirements and improve workflows. You may also participate in regular code reviews and contribute to the ongoing improvement of data infrastructure. This role is ideal for problem-solvers who enjoy working with both code and complex systems in a collaborative, fast-paced environment.

What engineers make 500,000?

Senior data engineers with extensive experience, specialized skills in cloud platforms, and advanced knowledge of data architecture can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large tech companies. Achieving this level often requires a combination of technical expertise, leadership roles, and sometimes stock options or bonuses.

What is a Data Engineering job?

A Data Engineering job involves designing, building, and maintaining the infrastructure that enables efficient data collection, storage, and processing. Data Engineers develop pipelines to transform raw data into usable formats for analytics and machine learning. They work with databases, big data technologies, and cloud platforms to ensure data is accessible and reliable. Their role is crucial for organizations to make data-driven decisions and optimize business processes.

Are data engineers still in demand?

Data engineers are currently in high demand due to the increasing reliance on data-driven decision making and the growth of big data technologies. They typically require skills in SQL, cloud platforms, and data pipeline tools like Apache Spark or Kafka, making their expertise valuable across many industries. The role is expected to remain strong as organizations continue to prioritize data infrastructure and analytics capabilities.

What are the key skills and qualifications needed to thrive in the Data Engineering position, and why are they important?

To thrive in Data Engineering, you need a solid background in programming (such as Python, Java, or Scala), data modeling, and database management, typically supported by a degree in computer science or a related field. Familiarity with ETL tools, cloud platforms like AWS or Azure, big data frameworks (e.g., Hadoop, Spark), and relevant certifications is highly valued. Strong problem-solving abilities, effective communication, and the ability to work collaboratively across teams are key soft skills for this role. These attributes are crucial for designing robust data pipelines, ensuring data quality, and enabling organizations to make data-driven decisions efficiently.

What cities are hiring for Data Engineering jobs? Cities with the most Data Engineering job openings:
What are the most commonly searched types of Data Engineering jobs? The most popular types of Data Engineering jobs are:
What states have the most Data Engineering jobs? States with the most job openings for Data Engineering jobs include:
What job categories do people searching Data Engineering jobs look for? The top searched job categories for Data Engineering jobs are:
Infographic showing various Data Engineering job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.
Data Engineering Lead

$131K - $158K/yr

Other

Posted 3 days ago


Accenture Federal Services rating

8.4

Company rating: 8.4 out of 10

Based on 19 frontline employees who took The Breakroom Quiz

48th of 437 rated business services


Job description

Job Description

The Data Engineer will design, build, and maintain the core client data infrastructure and pipelines necessary to ingest, process, store, and transform data for various consumers. Develop and operate automated, end-to-end data pipelines, create and maintain data models and schemas, and contribute to the overall scalability, reliability, and security of the data platform. Implement data processing frameworks and technologies, design and optimize data storage solutions, and develop data transformation logic to support analytics requirements. Implement data quality checks and validation procedures, establish data lineage tracking mechanisms, and troubleshoot data pipeline issues. Collaborate with data scientists and analysts to understand data requirements, work with security teams to implement data protection measures, and stay current with data engineering technologies and best practices. Document data architecture and pipelines, participate in data governance activities, and contribute to continuous improvement of data engineering processes.

Must have:

  • 8 years of experience in data engineering, data pipeline design, and management
  • Must meet DoD 8140 requirements
  • Bachelor's degree (or 4 years of additional equivalent experience) in IT, Cybersecurity, Computer Science, Information Systems, Data Science, Software Engineering

Security Clearance:

  • Active Secret, Top Secret, TS/SCI, or TS/SCI with Polygraph clearance required, depending on position 

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