840 Data Engineer Professional Services jobs in Plano,TX

Applied Early Career Program - Field Service Engineer

Applied Materials

Dallas, TX 75221

Paid Relocation to Dallas, TX

Requires Travel

Associate degree, recent college graduate, military technical training, trade certification, or equivalent hands-on experience
Basic mechanical aptitude and interest in technical systems
Willingness to learn and read electrical and mechanical schematics
Ability to diagnose and solve basic technical problems
Strong written and verbal communication skills
Basic working knowledge of Microsoft Excel, Word, and PowerPoint
Valid driver's license and ability to obtain a passport, if required for travel
Ability to meet on-site safety, environmental, and customer requirements

SmartExplore AI is experimental.

New, Posted 16 hours ago

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ResumeLibrary

Sr. Data Engineer

McKesson

Irving, TX 75039

$141,336-$184,400/yr

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Manufacturing Engineer

DEAN TECHNOLOGY

Addison, TX 75001

OnsiteHealth InsuranceRetirement Benefit

Education: BSEE/BSME/BSMechE and 5+ years' experience, or the equivalent of 10 years' experience in manufacturing engineering, with electronics background.
Skills / Technical Knowledge / Experience: Working knowledge of mechanical assemblies, tooling, fixtures, tolerances, and assembly drawings.
Skills / Technical Knowledge / Experience: Requires knowledge of fabrication processes, material specification, and general industrial operations.
Skills / Technical Knowledge / Experience: Must be a business minded engineer to provide continuous improvements to products and processes.
Skills / Technical Knowledge / Experience: Must be proficient with program management tools and have the ability to manage and prioritize multiple projects, tasks, and assignments at once.
Must be eligible to work in the United States without sponsorship.

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New, Posted just now

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Business Intelligence Data Engineer

Golden State Foods

Frisco, TX 75034

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Senior Specialist, Manufacturing Engineering

L3 Harris

Richardson, TX 75080

~ 17 min OnsiteBilingual Preferred

Bachelor's Degree and minimum 6 years of prior Manufacturing Engineering experience
Graduate Degree and a minimum of 4 years of prior Manufacturing Engineering experience
In lieu of a degree, minimum of 10 years of prior Manufacturing Engineering experience
Security clearances may only be granted to U.S. citizens
All applicants will be considered for employment without regard to race, color, religion, age, national origin, ancestry, ethnicity, gender (including pregnancy, childbirth, breastfeeding or other related medical conditions), gender identity, gender expression, sexual orientation, marital status, veteran status, disability, genetic information, citizenship status, characteristic or membership in any other group protected by federal, state or local laws
L3Harris maintains a drug-free workplace and performs pre-employment substance abuse testing and background checks, where permitted by law
L3Harris is proud to be an Equal Opportunity Employer

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Principal Engineer - Python API Development

Fidelity Investments

Irving, TX 75061

~ 35 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's or Master's degree in Computer Science, Software Engineering, or a closely related engineering discipline
8+ years (typically 10+) building and operating production platforms and services at scale
Deep software engineering expertise in Python and distributed systems
A track record of building production‑grade services, libraries, and internal platforms
Linux fluency and scripting are required
Cloud platform leadership (AWS) —hands-on with S3, Lambda, Batch, Step Functions, EventBridge, CloudWatch, and SNS/SQS—and experience shaping platform patterns that other teams adopt
Experience enabling managed ML services (e.g., SageMaker) as part of broader platform capabilities; exposure to Azure or GCP is beneficial
DevOps and CI/CD at scale, owning standards for automated build/test/deploy (e.g., Jenkins, Git‑based workflows), containerization (Docker), release governance, and multi‑environment promotion for ML‑enabled workloads
Infrastructure as Code (CloudFormation, Terraform/OpenTofu) and platform reliability engineering (SLOs/error budgets, capacity planning, cost observability, incident response, and post‑mortems) for ML serving and data/feature pipelines
ML enablement in production: model packaging, deployment strategies (batch/online/streaming), inference routing, traffic management, performance tuning, observability, and controls for responsible use—without a research or modeling focus
Cross‑org technical leadership: you mentor junior and senior engineers, are a backbone of code review across repos, and routinely consider impacts on upstream/downstream systems when proposing changes
Set platform strategy and standards for ML packaging, deployment, serving, and observability—driving consistent adoption across squads and business units
Partner with Data Scientists to package, scale, and operationalize models; define the APIs, guardrails, and automation that take work from experimentation to reliable production
Enable secure, scalable access to traditional and generative models by collaborating with platform and application engineers to integrate through enterprise gateways and services
Advance model/data observability—tooling for data and feature drift detection, prediction‑quality monitoring and uncertainty signals, and automated diagnostics/ explainability
Lead cross‑platform incident response and post‑mortems, drive systemic fixes, and evolve standards to prevent recurrence—across applications and the platform
Uplevel engineering velocity by introducing reusable frameworks, paved paths, and CI/CD templates that simplify integration, reduce toil, and improve reliability at scale
Reduce cost and complexity across the ML ecosystem through pragmatic technology choices, clear abstractions, and a long‑term platform roadmap
The base salary range for this position is $107,000-216,000 USD per year.
Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.

SmartExplore AI is experimental.

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EPIC ODB Engineer / Architect - Remote

NTT DATA Americas

Plano, TX 75086

Remote

7–10+ years of experience supporting Epic as an ODBA, DBA, or database architect.
Epic certifications in Chronicles, ODBA, or related technical modules (e.g., Cache/IRIS).
7–10+ years ofDeep expertise with InterSystems Caché/IRIS, including globals, journaling, shadowing, and performance tuning.
7–10+ years of strong understanding of Epic architecture, including Hyperspace, Interconnect, Web Blob, and ancillary systems.
7–10+ years of Proficiency with Linux/UNIX administration and shell scripting.
7–10+ years of Experience with high‑availability architectures, clustering, SAN/NAS storage, and virtualization.
7–10+ years of Strong analytical and troubleshooting skills for complex, high‑volume clinical systems.

SmartExplore AI is experimental.

New, Posted 1 day ago

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Applied Early Career Program - Field Service Engineer

Applied Materials

Dallas, TX 75221

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Manufacturing Engineer Asc (Level 1)

Lockheed Martin

Grand Prairie, TX 75051

~ 44 min OnsiteFlexible SchedulePaid Time Off

Bachelor's degree in Manufacturing Engineering Technology, a similar field, or equivalent experience
Proven track record of data driven approach to solving problems
Strong communication skills
MUST BE A U.S. CITIZEN
This position is located at a facility that requires special access
The selected candidate must be able to obtain a Secret clearance
Security Clearance Statement: This position requires a government security clearance, you must be a US Citizen for consideration.
Clearance Level: Secret
Onsite Full-time: The work associated with this position will be performed onsite at a designated Lockheed Martin facility.
Schedule for this Position: 4x10 hour day, 3 days off per week
Relocation Available: Possible

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Principal Engineer - Python API Development

Fidelity Investments

Lewisville, TX 75029

~ 32 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's or Master's degree in Computer Science, Software Engineering, or a closely related engineering discipline
8+ years (typically 10+) building and operating production platforms and services at scale
Deep software engineering expertise in Python and distributed systems
A track record of building production‑grade services, libraries, and internal platforms
Linux fluency and scripting are required
Cloud platform leadership (AWS) —hands-on with S3, Lambda, Batch, Step Functions, EventBridge, CloudWatch, and SNS/SQS—and experience shaping platform patterns that other teams adopt
Experience enabling managed ML services (e.g., SageMaker) as part of broader platform capabilities; exposure to Azure or GCP is beneficial
DevOps and CI/CD at scale, owning standards for automated build/test/deploy (e.g., Jenkins, Git‑based workflows), containerization (Docker), release governance, and multi‑environment promotion for ML‑enabled workloads
Infrastructure as Code (CloudFormation, Terraform/OpenTofu) and platform reliability engineering (SLOs/error budgets, capacity planning, cost observability, incident response, and post‑mortems) for ML serving and data/feature pipelines
ML enablement in production: model packaging, deployment strategies (batch/online/streaming), inference routing, traffic management, performance tuning, observability, and controls for responsible use—without a research or modeling focus
Cross‑org technical leadership: you mentor junior and senior engineers, are a backbone of code review across repos, and routinely consider impacts on upstream/downstream systems when proposing changes
Set platform strategy and standards for ML packaging, deployment, serving, and observability—driving consistent adoption across squads and business units
Partner with Data Scientists to package, scale, and operationalize models; define the APIs, guardrails, and automation that take work from experimentation to reliable production
Enable secure, scalable access to traditional and generative models by collaborating with platform and application engineers to integrate through enterprise gateways and services
Advance model/data observability—tooling for data and feature drift detection, prediction‑quality monitoring and uncertainty signals, and automated diagnostics/ explainability
Lead cross‑platform incident response and post‑mortems, drive systemic fixes, and evolve standards to prevent recurrence—across applications and the platform
Uplevel engineering velocity by introducing reusable frameworks, paved paths, and CI/CD templates that simplify integration, reduce toil, and improve reliability at scale
Reduce cost and complexity across the ML ecosystem through pragmatic technology choices, clear abstractions, and a long‑term platform roadmap
The base salary range for this position is $107,000-216,000 USD per year.
Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.