ZipRecruiter

Log In

2

Full Time Data Engineering Jobs (NOW HIRING)

FairSquare

Director of Data Engineering

San Diego, CA · Hybrid

$170K - $230K/yr

Director of Data Engineering - San Diego, CA 3 days/week in office, 2 days/week remote, Full time M-F Being authorized to work in the U.S. is a precondition of employment. FairSquare does not ...

Doximity

Data Engineering Manager

San Francisco, CA · On-site +1

$172K - $254K/yr

Collaborate with product managers, data analysts, and machine learning engineers to develop ... More on /Benefits/Perks Doximity is proud to offer industry-leading benefits to our full time ...

Fair Square

Director of Data Engineering

San Diego, CA · On-site

$170K - $230K/yr

Director of Data Engineering - San Diego, CA • 3 days/week in office, 2 days/week remote, Full time M-F • Being authorized to work in the U.S. is a precondition of employment. • FairSquare does ...

Kharon

Data Engineer

Denver, CO

$120K - $160K/yr

DR Kharon is seeking a full-time Data Engineer based in Denver, Colorado. This role requires in-office attendance 3 days a week. RESPONSIBILITIES: * Help build large-scale distributed automated data ...

next page

Showing results 1-20

All JobsData Engineering JobsFull Time Data Engineering Jobs

Full Time Data Engineering information

See salary details

$44.5K

$129.7K

$177.5K

How much do full time data engineering jobs pay per year?

As of Jul 22, 2026, the average yearly pay for full time data engineering 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.

Is there a high demand for data engineers?

Data engineering is a highly sought-after role due to the increasing reliance on data-driven decision making across industries. The demand for skilled data engineers with expertise in tools like SQL, Python, and cloud platforms continues to grow, leading to strong job prospects and competitive salaries.

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 engineer makes $500,000 a year?

Senior data engineers with extensive experience, advanced skills in cloud platforms, and expertise in big data tools can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large tech companies. Such compensation often includes bonuses, stock options, and other incentives.

What engineers make $300,000 a year?

Senior data engineers with extensive experience, advanced skills in cloud platforms, and expertise in big data tools can earn $300,000 or more annually. High compensation is often associated with roles in large organizations, specialized expertise, and leadership responsibilities in data infrastructure projects.

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

To thrive as a Full Time Data Engineer, you need strong programming skills (such as Python or Java), proficiency in SQL, and a solid understanding of data modeling and ETL processes, usually supported by a degree in computer science or a related field. Familiarity with big data tools (like Hadoop or Spark), cloud platforms (such as AWS or Azure), and relevant certifications (e.g., Google Cloud Data Engineer) is highly valuable. Excellent problem-solving, communication, and teamwork abilities distinguish top performers in this role. These skills ensure efficient data infrastructure development, reliable data pipelines, and effective collaboration with cross-functional teams to support business objectives.

What are full time data engineering jobs?

Full time data engineering jobs involve building, managing, and optimizing data pipelines and infrastructure to collect, process, and store large volumes of data for organizations. Data engineers work with technologies like SQL, Python, cloud platforms, and big data tools to ensure data is reliable and accessible for analytics and business decision-making. These roles typically require strong programming skills, knowledge of database systems, and experience with data modeling and ETL (Extract, Transform, Load) processes. Full time positions generally offer benefits and require a standard workweek commitment, often in tech, finance, healthcare, or other data-driven industries.

What is the difference between Full Time Data Engineering vs Part Time Data Engineering?

AspectFull Time Data EngineeringPart Time Data Engineering
Work HoursTypically 40 hours/weekLess than 20 hours/week
CredentialsRelevant degrees, certifications like AWS, GCP, or AzureSame as full-time, but often less emphasis on certifications
Work EnvironmentFull-time employment, often in corporate or tech firmsFreelance or contract basis, flexible locations
Job ResponsibilitiesDesigning, building, maintaining data pipelinesSupporting existing pipelines, smaller projects

Full Time Data Engineering involves a standard 40-hour workweek with comprehensive responsibilities in designing and maintaining data systems. Part Time Data Engineering offers flexible hours, often focusing on specific tasks or projects. Both roles require relevant technical skills and certifications, but full-time positions typically demand more extensive experience and commitment.

What are some common challenges faced by full-time data engineers, and how can they be addressed?

Full-time data engineers often encounter challenges such as integrating data from diverse sources, ensuring data quality, and optimizing data pipelines for scalability and performance. These issues can be addressed by adopting robust ETL (Extract, Transform, Load) frameworks, implementing automated data validation tests, and collaborating closely with data analysts and software engineers to align on data requirements. Staying updated with the latest cloud technologies and best practices in data architecture also helps in overcoming these challenges and maintaining efficient, reliable data systems.
What cities are hiring for Full Time Data Engineering jobs? Cities with the most Full Time 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 Full Time Data Engineering jobs? States with the most job openings for Full Time Data Engineering jobs include:
Full Time Data Engineering jobs near you

Manager, Data Engineering

Starcom Mediavest Group Germany Gmbh

Philadelphia, PA

$88K - $127K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 7 days ago

Job description

Company Description

PHM is the leading health media agency in the US, built for the modern healthcare experience. Here, industry depth meets media scale, where data becomes direction, where creativity and storytelling bring truth to life, and where orchestration replaces fragmentation.

Dedicated to making brands discovered, PHM redefines what media can do through data, content, and creativity. Because in modern healthcare, the brands that are found are the ones that lead. And when brands lead, advantage follows. Go deeper. Be found.

Job Description

The Data Manager of Data Engineering will work in a hands-on and supportive role in our Technology and Data Department. This team processes and maintains all the data that flows into our organization and is the face of the agency regarding data needs from HCP publishers.

You will work with internal and external partners, along with industry vendors, to monitor data transfers, perform data QA'ing and maintain documentation. You will also support the Vice President of Data engineering to enforce enterprise-wide data processes and protocols.

Responsibilities
  • Lead a portfolio of data projects across multiple clients
  • Design and manage scalable pipelines, including ingestion from APIs (REST, GraphQL, vendor feeds) and traditional ETL sources
  • Contribute to data architecture decisions to ensure efficient schema design, scalability, and governance across data warehouses and lakehouses
  • Partner with BI, Product, and Media Tech teams to automate data integrations and improve data flow reliability
  • Oversee ETL and metadata management to ensure stability, security, and compliance
  • Present issues, trends, and recommendations to internal and external stakeholders
  • Maintain best practices for handling, storing, and governing data
Qualifications
  • BS in Computer Science, Information Technology, or related field
  • Strong hands-on experience with PySpark (preferred language for data engineering and automation)
  • Proficiency in Python and SQL for data processing and automation
  • Experience building and maintaining API-based data pipelines, including authentication and error handling
  • Solid knowledge of modern data architecture (data modeling, governance, warehouse, lakehouse)
  • Experience with database structures, ETL, and cloud data platforms
  • Technical documentation skills and ability to communicate complex topics in simple, user-friendly terms

Specific Skills Required:

  • Cloud platforms: AWS, Azure, Databricks
  • Data warehouses/lakehouses: Snowflake, Redshift, Databricks Lakehouse
  • BI tools: Tableau, Datorama (preferred)
  • Strong collaboration skills with cross-functional teams
Additional Information

Our Publicis Groupe motto "Viva La Difference" means we're better together, and we believe that our differences make us stronger. It means we honor and celebrate all identities, across all facets of intersectionality, and it underpins all that we do as an organization. We are focused on fostering belonging and creating equitable & inclusive experiences for all talent.

Publicis Groupe provides robust and inclusive benefit programs and policies to support the evolving and diverse needs of our talent and enable every person to grow and thrive. Our benefits package includes medical coverage, dental, vision, disability, 401K, as well as parental and family care leave, family forming assistance, tuition reimbursement, and flexible time off.

If you require accommodation or assistance with the application or onboarding process specifically, please contact USMTTACompliance@publicis.com.

All your information will be kept confidential according to EEO guidelines.

 Compensation Range: USD $88,540.00 - USD $127,155.00/Annually. This is the pay range the Company believes it will pay for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan through a third-party benefits administration system once certain criteria have been met. Temporary roles may also qualify for participation in our 401(k) plan after eligibility criteria have been met. For regular roles, the Company will offer medical coverage, dental, vision, disability, 401k, and paid time off. The Company anticipates the application deadline for this job posting will be 7/20/2026.Employment Type: FULL_TIME

Apply