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Full Time Data Acquisition Engineer information

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$165K

$243.5K

How much do full time data acquisition engineer jobs pay per year?

As of Jul 19, 2026, the average yearly pay for full time data acquisition engineer 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.

What is the difference between Full Time Data Acquisition Engineer vs Data Analyst?

AspectFull Time Data Acquisition EngineerData Analyst
Required CredentialsBachelor's in Engineering, Computer Science, or related field; experience with data collection toolsBachelor's in Statistics, Mathematics, or related field; proficiency in data analysis software
Work EnvironmentFieldwork, laboratory, or industrial settings; focus on data collection hardware and systemsOffice-based; focus on data interpretation and reporting
Employer & Industry UsageManufacturing, energy, telecommunications, research institutionsBusiness, finance, marketing, healthcare sectors

While both roles involve working with data, a Full Time Data Acquisition Engineer primarily focuses on collecting and maintaining data through hardware and systems in technical environments. In contrast, a Data Analyst interprets and visualizes data to support decision-making. The roles often overlap in data handling but differ in their core responsibilities and work settings.

What are Full Time Data Acquisition Engineers?

Full Time Data Acquisition Engineers are professionals responsible for designing, implementing, and maintaining systems that collect and manage data from various sources, such as sensors, machines, or digital platforms. They work to ensure that data is accurately gathered, processed, and made accessible for analysis and decision-making. These engineers often collaborate with software developers, analysts, and hardware teams to create efficient data pipelines. Their role is crucial in industries like manufacturing, automotive, research, and technology, where reliable data is essential for monitoring, control, and innovation.

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

To excel as a Full Time Data Acquisition Engineer, you need a solid background in electrical or computer engineering, data collection methodologies, and signal processing, usually supported by a relevant bachelor's degree. Familiarity with data acquisition hardware, programming languages such as Python or LabVIEW, and working knowledge of DAQ systems and sensors is typically required. Strong analytical thinking, problem-solving skills, and effective communication are valuable soft skills for collaborating with multidisciplinary teams and interpreting complex data. Mastery of these skills ensures accurate and efficient data collection, supporting critical decision-making and system optimization.

What are some common challenges Full Time Data Acquisition Engineers face when integrating data from multiple sources?

Full Time Data Acquisition Engineers often encounter challenges such as inconsistent data formats, varying data quality, and differing update frequencies when integrating data from multiple sources. Addressing these issues typically requires close collaboration with other engineering teams and stakeholders to establish standardized protocols and robust validation processes. Additionally, engineers must be proactive in troubleshooting connectivity issues and ensuring data security throughout the acquisition pipeline. Overcoming these challenges is essential for delivering reliable, actionable data to downstream systems and users.
More about Full Time Data Acquisition Engineer jobs
What cities are hiring for Full Time Data Acquisition Engineer jobs? Cities with the most Full Time Data Acquisition Engineer job openings:
What are the most commonly searched types of Data Acquisition Engineer jobs? The most popular types of Data Acquisition Engineer jobs are:
What job categories do people searching Full Time Data Acquisition Engineer jobs look for? The top searched job categories for Full Time Data Acquisition Engineer jobs are:
Full Time Data Acquisition Engineer jobs near you
Infographic showing various Full Time Data Acquisition Engineer job openings in the United States as of July 2026, with employment types broken down into 87% Full Time, 9% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $165,018 per year, or $79.3 per hour.
Sr Manager Software Engineering - Data Acquisition

Sr Manager Software Engineering - Data Acquisition

WEX

Remote

Full-time

This job post has expired today. Applications are no longer accepted.

WEX Inc. rating

7.3

Company rating: 7.3 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

14th of 20 rated payment service providers

Job description

Job Summary:
WEX is a leading company focused on Data-as-a-Service, and they are seeking a hands-on Senior Manager, Software Engineering - Data Acquisition to lead their team. The role involves overseeing the acquisition and processing of high-volume data while driving the evolution toward AI-augmented software development to enhance platform scalability and delivery speed.
Responsibilities:
• Recruit, mentor, and lead a high-performing team of software engineers focused on data acquisition, fostering a collaborative and inclusive culture. Oversee performance management, career pathing, and top-tier talent acquisition.
• Pioneer the adoption of AI-assisted software development across engineering teams. Define metrics and implement AI-enabled development workflows to measurably enhance engineering productivity.
• Establish and enforce a specification-first development methodology. Standardize templates for all key artifacts (APIs, data contracts, ingestion pipelines, architecture) and ensure end-to-end traceability across implementation, validation, deployment, and observability.
• Drive the migration to automated, metadata-driven, and declarative engineering architectures. Develop reusable frameworks that translate technical specifications directly into generated code, deployment artifacts, and operational controls.
• Define and execute the technical roadmap for all data acquisition pipelines and systems, ensuring the infrastructure is highly scalable, reliable, secure, and cost-effective to accommodate accelerating data volume and velocity.
• Provide authoritative technical direction on the design, development, and maintenance of mission-critical data ingestion frameworks. Mandate and enforce best practices for software engineering, data governance, and data quality.
• Partner closely with Product Management, Data Science, Data Governance, and other engineering teams to align data solutions with overarching business requirements and strategic data needs.
• Institute and champion continuous improvement in engineering processes, tools, and methodologies, including CI/CD, automation, monitoring, and alerting practices.
• Guarantee the high availability and performance of all data acquisition systems, taking ownership of incident response, recovery, and thorough root cause analysis for major service disruptions.
• Oversee budget allocation, resource management, and capacity planning to ensure the strategic growth of the data acquisition organization.
Qualifications:
Required:
• Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.
• 10+ years of experience in software engineering, with at least 5+ years in a management role overseeing software engineering or data acquisition teams.
• Experience in leading virtual teams is highly desirable.
• Experience implementing AI-assisted engineering workflows in production software organizations.
• Deep understanding of specification-driven engineering, declarative system design, or model-driven development.
• Deep expertise in building and managing high-volume, real-time and batch data pipelines (e.g., Kafka, Kinesis, Pulsar).
• Proficiency with cloud platforms (e.g., AWS, Azure, GCP) and experience designing scalable, serverless, or containerized data ingestion architectures (e.g., Kubernetes, EKS/AKS/GKE).
• Strong knowledge of various data sources, integration patterns (APIs, web scraping, messaging queues), and ETL/ELT tools.
• Expertise in programming languages such as Java, Python, Scala, or Go.
• Solid understanding of database technologies (SQL, NoSQL, Data Warehouses like Snowflake, Redshift, etc.).
• Proven ability to lead, motivate, and manage multiple distributed teams.
• Excellent communication, presentation, and interpersonal skills.
• Strong analytical and problem-solving skills, with the ability to define solutions for complex technical challenges.
Company:
Wex is a financial technology service provider for fleet, travel and healthcare industries. Founded in 1983, the company is headquartered in Portland, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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