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Data Engineering Specialist Jobs (NOW HIRING)

ClifyX

Senior Specialist - Data Engineering

Chicago, IL · On-site

$109K - $148K/yr

ClifyX is seeking a Senior Specialist in Data Engineering. The role requires proficiency in Snowflake and Azure, along with strong SQL and Python skills for data manipulation and automation, and ...

DXC Technology

Data Engineering Lead

Charleston, SC · On-site

Lead and mentor a team of Data Engineers, Data Architects, and Data Integration specialists. * Establish engineering best practices and technical standards. * Provide technical oversight ...

City of Pharr

Broadband Engineering Specialist

Pharr, TX · On-site

$40K/yr

... with data security regulations, all while contributing to the growth of Pharr's broadband ... Are you the Broadband Engineering Specialist we're looking for? To excel as a Full Time Broadband ...

Group O

Reliability Engineering Specialist

Fort Worth, TX · On-site

$50K - $80K/yr

Reliability Engineering Specialist Department: Engineering Employment Type: Full Time Location ... Analyzes reliability and production data to identify trends, determine root causes, and drive ...

International Executive Service Corps

$150 - $200/hr

The Senior Engineering Specialist will provide engineering services to include design review ... Ensure timely input of all data, comments, and documentation into MAXIMO software project ...

Saipem

Maint. Engineering Specialist

Milan, MI · On-site

... data from technical disciplines and vendors to build-up a comprehensive plant asset register which includes all the maintainable equipment, * preparation of Maintainable Equipment List (MEL ...

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All JobsData Engineering Specialist Jobs

Data Engineering Specialist information

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$33K

$81.5K

$140K

How much do data engineering specialist jobs pay per year?

As of Sep 8, 2026, the average yearly pay for data engineering specialist in the United States is $81,518.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,500.00 and $96,500.00 per year, depending on experience, location, and employer.

What is a data engineering specialist?

Data Engineering Specialists are professionals who design, build, and maintain the infrastructure that allows organizations to collect, store, and analyze large amounts of data. They develop data pipelines, manage databases, and ensure data is accessible, reliable, and secure for analytics and business intelligence purposes. Their work is crucial in transforming raw data into usable formats for data scientists, analysts, and business leaders.

How does a data engineering specialist typically collaborate with data scientists and analysts within an organization?

Data Engineering Specialists work closely with data scientists and analysts by designing, building, and maintaining data pipelines that ensure reliable, high-quality data is readily available. They often meet regularly with these teams to understand data requirements, troubleshoot data issues, and optimize workflows for analytics and machine learning projects. Effective collaboration involves clear communication about data structures, definitions, and timelines, as well as actively participating in code reviews and joint problem-solving sessions. This teamwork is essential for delivering impactful, data-driven solutions across the organization.

What are the key skills and qualifications needed to thrive as a data engineering specialist, and why are they important?

To thrive as a Data Engineering Specialist, you need expertise in database management, data modeling, ETL processes, and programming languages such as SQL, Python, or Scala, often supported by a degree in computer science or a related field. Proficiency with big data platforms (e.g., Hadoop, Spark), cloud services (AWS, Azure, GCP), and data pipeline orchestration tools is typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help you collaborate with cross-functional teams and address complex data challenges. These skills are essential for building robust, scalable data infrastructure that empowers organizations to make data-driven decisions.

What is the difference between Data Engineering Specialist vs Data Engineer?

AspectData Engineering SpecialistData Engineer
CredentialsBachelor's in CS, certifications like AWS, GCP, or AzureBachelor's in CS, related certifications
Work EnvironmentData teams, cloud platforms, data warehousesData pipelines, databases, cloud environments
Industry UsageUsed across tech, finance, healthcareCommon in similar industries, focus on data infrastructure
Search IntentUnderstanding roles, skills, and career pathJob requirements, skills, and responsibilities

Data Engineering Specialists focus on designing and maintaining data pipelines, often with specialized skills in cloud platforms. Data Engineers build and optimize data infrastructure, working on data collection, storage, and processing. Both roles overlap in skills and environment but differ in scope and focus.

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What are popular job titles related to Data Engineering Specialist jobs?

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Data Engineering Specialist jobs near you
Infographic showing various Data Engineering Specialist job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $81,518 per year, or $39.2 per hour.

Manager, Data Engineering

Manhattan, NY • On-site

Building Service 32BJ Benefit Funds
Civic and Social Organizations • 201 - 500 employees
Learn more about Building Service 32BJ Benefit Fundsexternal

$140K - $150K/yr

Full-time

Medical, Retirement

Re-posted 18 days ago

Job description

Job Code
911

Department Name
Health Fund Admin

Reports To
Assistant Director, Health Analytics & Engineering

FLSA Status
Exempt

Union Code
N/A

Management
Yes


About Us:

Building Services 32BJ Benefit Funds (“the Funds”) is the umbrella organization responsible for administering Health, Pension, Retirement Savings, Training, and Legal Services benefits to over 185,000 SEIU 32BJ members. Our mission is to make significant contributions to the lives of our members by providing high quality benefits and services. Through our commitment, we embody five core values: Flexibility, Initiative, Respect, Sustainability, and Teamwork (FIRST). By following our core values, employees are open to different and new ways of doing things, take active steps to improve the organization, create an environment of trust and respect, approach their work with the intent of a positive outcome, and work collaboratively with colleagues.


The Funds oversees and manages $11 billion of dollars in assets, which are made up of many, varied and complex funds. The dollars come from a number of sources, including the property owners who pay into the funds on behalf of their employees, and as such, requires those who oversee and manage the money to be highly skilled financial management people.


32BJ Benefit Funds will continue to drive innovation, equity, and technology insights to further help the lives of our hard-working members and their families. We use cutting edge technology such as: M365, Dynamics 365 CRM, Dynamics 365 F&O, Azure, AWS, SQL, Snowflake, QlikView, and more.


Please take a moment to watch our video to learn more about our culture and contributions to our members: youtu.be/hYNdMGLn19A


Job Summary:

Under the direction of the Assistant Director, Health Analytics & Engineering, the Manager, Data Engineering provides technical leadership and oversight for the Health Fund's Data Engineering Team, including the enterprise data warehouse, system integrations, data pipelines, and data governance frameworks. The role leads a team of data engineering professionals responsible for delivering scalable, secure, and high-quality data solutions that support reporting, analytics, operational processes, and strategic initiatives. 


The Manager, Data Engineering oversee numerous projects and initiatives across the full data lifecycle, including data governance, ETL processes, data validation, standardization and normalization, data integrity and quality assurance/control (QA/QC), data integration, and reporting and dashboard solutions. This position operates at both a technical and business level, helping to delineate roles and responsibilities across the Data Engineering Team while minimizing operational friction and delivering high-quality, reliable technical products in line with business needs and expectations. Working closely with internal teams, including Data Engineering, Analytics, IT, and other stakeholders, as well as external data vendors and content providers, this position drives the delivery of high-quality data products, establishes best practices for data management and governance, and ensures data platforms meet evolving business, regulatory, privacy, and security requirements.


Essential Duties and Responsibilities:

  • Oversee the Data Engineering Team through leadership and supervision. Staff may include Data Engineers, ETL Specialists, and other relevant technical staff.
  • Provide leadership, coaching, performance management, and professional development to Data Engineering staff, fostering a collaborative, accountable, and high-performing team environment.
  • Technical ownership of the data warehouse, including system architecture, data architecture, data engineering, and data pipelines
  • Lead collaboration for the deployment and implementation of tools necessary to integrate data within and across information systems and support data-driven decision­ making.
  • Understand business requirements and translate them into technical solutions and application features.
  • Develop and implement methods to improve data reliability, quality, and accessibility.
  • Maintain data governance and documentation practices for a variety of data inputs from multiple sources, including flat files and spreadsheet-based files transmitted through SFTP, as well as JSON/XML style objects from API interfaces and other data exchange mechanisms.
  • Participate in the evaluation and pilot of new technologies and provide recommendations regarding their alignment with business needs and strategic objectives.
  • Manage communication and relationships with data platform stakeholders, balancing business requirements with technology capabilities.
  • Partner with business and technology leadership to develop and execute the Health Fund's data strategy, roadmap, and priorities, ensuring alignment with organizational goals and business objectives.
  • Develop testing protocols to ensure processes are robust and bugs are identified, documented, and resolved.
  • Conduct functional and non-functional testing.
  • Evaluate existing data models, architectures, and pipelines.
  • Develop and maintain technical documentation to accurately represent data models, architectures, integrations, and workflows.
  • Ensure that integration processes are fully tested and any issues, limitations, integrations, or dependencies are well defined and documented.
  • Work with cross-functional technology and business partners to lead the technical delivery of integration solutions approved within the portfolio and contribute to the ongoing development of the Funds' data strategy
  • Collaborate with business partners and internal teams to understand, document, prioritize and implement new datasets, integrations, and features within the data warehouse environment.
  • Align closely with agency IT teams to support the deployment of integration systems.
  • Partner with the QA and Infrastructure teams to ensure compliance with regulatory and security requirements.
  • Establish, maintain, and enforce data engineering standards, policies, procedures, and best practices to ensure data quality, scalability, security, reliability, and operational efficiency.
  • Monitor and optimize the performance, availability, and reliability of data platforms, data pipelines, data warehouse environments, and integration processes to support business continuity and operational effectiveness.
  • Collaborate with Data Warehouse Architect in the design for the overall architecture of the data platforms and provide guidance and oversight.
  • Ensure that guiding principles, technology standards, data governance requirements, and privacy policies are consistently followed.


Qualifications (Competencies):

  • Minimum 8 years of experience in data engineering, data warehousing, ETL/ELT development, data integration, or related technical disciplines.
  • Minimum 3 years of management or supervisory experience leading technical teams and complex data initiatives.
  • Experience managing projects across the full data lifecycle, including data governance, data quality, integration, testing, documentation, and production support.
  • Knowledge of healthcare regulatory requirements and data governance standards affecting health benefits organizations preferred.
  • Familiarity of HIPAA privacy and security requirements and their application to healthcare data environments preferred.
  • Advanced knowledge of data warehouse design, data modeling, and ETL/ELT methodologies preferred.
  • Proficiency in SQL and Python, with hands-on industry experience is a must.