1152 Data Engineer Da C Python jobs in Dallas,TX

Lead Software Engineer (Python, Invoice/BIlling)

Gartner

Irving, TX 75039

New, Posted 1 day ago

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DAS Field Manager

Communication Technology Services

Carrollton, TX 75006

~ 27 min Onsite

High School Diploma or GED.
Clean driving record.
Must pass a background check.
Physical ability to: carry tools, materials, & ladders; climb ladders, lift up to 50lb as-needed, and perform daily required tasks.

SmartExplore AI is experimental.

New, Posted 22 hours ago

Recommended

ResumeLibrary

Sr. Data Engineer

McKesson

Irving, TX 75039

$141,336-$184,400/yr

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Principal Engineer - Python API Development

Fidelity Investments

Irving, TX 75061

~ 22 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

Apply Directly

DAS Project Manager-Dallas

Communication Technology Services (CTS)

Carrollton, TX 75006

~ 27 min Onsite

Bachelor's Degree or equivalent work experience.
Three (3) to Five (5) years of project management experience with strong technical background, preferably in the fields of telecommunication or engineering.
Customer-facing project management experience.
Advanced knowledge of Telecommunications and/or Wireless Project Management.
Strong background in either DAS, Small Cell, Macro, Fiber, or Low voltage or Construction.
Ability to interpret blueprints and other project documents.
Ability to define and track project financials.
Ability to interpret and create project schedules.
Ability to manage multiple projects simultaneously.
Ability to “think outside the box” and meet customer deadlines, perform as the “go-to” person for other CTS /customer issues.
Strong verbal and written communication skills.
Strong computer skills, Bluebeam, Microsoft Office suite (Excel, Word, Power Point, MS Project, Visio).
Proven ability to work in a fast-paced environment and adapt quickly to change.
Must be a self-motivated individual with ability to work independently and in team environments with a positive attitude.
Must be able to travel within the region with a valid driver's license.

SmartExplore AI is experimental.

New, Posted 1 day ago

Recommended

DiversityJobs

Lead Software Engineer (Python, AI) - AskGartner

Gartner

Irving, TX 75039

Apply Directly

Principal Engineer - Python API Development

Fidelity Investments

Euless, TX 76039

~ 28 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 5 hours ago

Recommended

Apply Directly

Business Intelligence Data Engineer

Golden State Foods

Frisco, TX 75034

Apply Directly

Actuarial Analyst II (Intermediate) – Forecasting Analytics

USAA

Plano, TX 75023

Paid Relocation to Plano, TX

RemoteUrgently HiringFlexible ScheduleHealth InsurancePaid Time OffRetirement Benefit

Bachelor's degree
2 years of actuarial or analytical business experience
3 Casualty Actuarial Society (CAS) exams
Intermediate knowledge of data analysis tools, data visualization, developing analysis queries and procedures in Python, R, SQL, SAS, BI tools or other analysis software, and relevant industry data & methods and ability to connect technical insights to business problems

SmartExplore AI is experimental.

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Manager, Credit Strategy for Auto Finance Analytics

OneMain Financial

Irving, TX 75062

Hybrid~ 22 minFlexible ScheduleEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's Degree (Graduate a plus) in a quantitative discipline, such as Engineering, Statistics, Economics, Data Analytics or Computer Science.
2+ years of experience in a data driven analytics environment; consumer lending preferred; Master's or PHD degrees may offset experience. 4+ years required
Advanced analytical skillset using tools such as SQL, SAS, Excel skills required; experience with multiple types of relational databases and/or querying languages is a plus such as R, Hive Python, Oracle, Unix are desired
Innovative and capable of developing a highly analytical approach to solving problems
Experience driving projects and presenting to senior management on results and ideas
Capability and willingness to learn new areas within the OneMain business and take on diverse projects

SmartExplore AI is experimental.