874 Data Engineer Professional Services jobs in Arlington,TX

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Applied Early Career Program - Field Service Engineer

Applied Materials - Dallas, TX

Applied Early Career Program - Field Service Engineer

Paid Relocation to Dallas, TX

Requires Travel

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Tool Planner / Manufacturing Engineer (Level 2)

Lockheed Martin

Grand Prairie, TX 75051

Hybrid~ 15 minFlexible Schedule

Bachelor's degree or equivalent experience
Ability to communicate effectively
High attention to detail
Knowledge of tool design
Microsoft Office experience
General knowledge of mechanical manufacturing processes
Experience with PLM, MRP, & ERP systems is preferred
Expression of Interest: By applying to this job, you are expressing interest in this position and could be considered for other career opportunities where similar skills and requirements have been identified as a match. Should this match be identified you may be contacted for this and future openings.
Schedule for this Position: 4x10 hour day, 3 days off per week
Relocation Available: Possible
Part-time Remote Telework: The employee selected for this position will work part of their work schedule remotely and part of their work schedule at a designated Lockheed Martin facility. The specific weekly schedule will be discussed during the hiring process.

SmartExplore AI is experimental.

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Principal Engineer - Python API Development

Fidelity Investments

Hurst, TX 76054

~ 29 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.

New, Posted 23 hours ago

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ResumeLibrary

Sr. Data Engineer

McKesson

Irving, TX 75039

$141,336-$184,400/yr

New, Posted 1 day ago

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DiversityJobs

Software Engineer (Agentic AI/Data Engineering)

Gartner

Irving, TX 75039

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Manufacturing Engineer Asc (Level 1)

Lockheed Martin

Grand Prairie, TX 75051

~ 15 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

SmartExplore AI is experimental.

Apply Directly

Principal Engineer - Python API Development

Fidelity Investments

Bedford, TX 76022

~ 31 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.

New, Posted 1 day ago

Recommended

DiversityJobs

Data Engineer - Production Support

Gartner

Irving, TX 75039

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Senior Manufacturing Engineer

Klein Tools

Mansfield, TX 76063

~ 19 min OnsiteHealth InsuranceRetirement Benefit

Bachelor of Science Degree in Mechanical, Electrical, or Industrial Engineering (appropriate for the assigned area) and five (5) year experience
Must possess basic knowledge of tooling design methods and machine tool programming
Ability to use Microsoft Office and CAD software
Ability to communicate effectively both orally and written
Ability to communicate and work as a team member

SmartExplore AI is experimental.

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Manufacturing Engineer III

OIL STATES INDUSTRIES

Arlington, TX 76001

OnsiteHealth InsurancePaid Time OffRetirement Benefit

BS in Engineering or related field with at least 5 years of related experience; or MS degree in Engineering or related field with at least 4 years of related experience; At least 10 years of related experience without a degree.
Advanced experience in: (a) manufacturing engineering direct support and (b) Product engineering
Advanced experience using SolidWorks and AutoCAD
Advanced understanding of metal properties (yield/machinability/weldability/hardenability)
Advanced experience with polymer based materials and associated molding processes
Must be able to work independently, handle multiple tasks/projects, and train others.
Advanced experience with the process of conceptualizing new tooling and equipment and produce fully realized and functional designs with drawings, proper strength rating, and operation procedures.
Excellent verbal communication and technical writing skills.
Occasional travel, including international travel
CITIZENSHIP REQUIREMENTS - By contractual requirements this position requires that all persons establish proof of US Citizenship. Dual Citizenship (US citizenship and citizenship of some other country) cannot be accepted. You will be required to provide original or certified copies of documents establishing your citizenship prior to consideration for this position.

SmartExplore AI is experimental.