1293 Hadoop Developer jobs in Dallas,TX

U.S. citizenship is required
Possess a current valid driver's license
Carry and use a firearm. Maintaining firearm proficiency is mandatory.
Be at least age 21 at the time of application and less than age 37 at the time you receive a conditional offer of employment, unless you have previous service in a Federal Civilian Law Enforcement position covered by special law enforcement or firefighter retirement provisions, including early or mandatory retirement. Applicants with veteran's preference must receive a conditional offer of employment prior to reaching age 40 to continue in the application process.
You must obtain a Top Secret Clearance and retain it during your career.
Possess uncorrected visual acuity of no worse than 20/100 binocular, possess corrected visual acuity of 20/20 or better in each eye.
Hearing loss, as measured by an audiometer, must not exceed 25 decibels (A.S.A. or equivalent I.S.O.) in either ear in the 500,1000 and 2000Hz ranges.
Submit to a drug test prior to your appointment and random drug testing while you occupy the position.
Complete 13 weeks of intensive training at the Federal Law Enforcement Training Center(FLETC) in Glynco, GA and 18 weeks of specialized training at the James J. Rowley Training Center in Laurel, MD.
Sign a mobility agreement stating your willingness to accept assignments anywhere within the United States and overseas.
Certify that you have registered with the Selective Service System or are exempt from having to do so, if you are a male applicant born after December 31, 1959.

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Analyst, IT Digital Experimentation

American Airlines

Fort Worth, TX 76101

~ 44 min Onsite

Bachelor's degree in Statistics, Applied Math, Computer Science, Economics, Engineering, or related field
Proficiency in Python, R or other relevant modern programming languages
Experience with digital experimentation and causal inference
Experience with SQL
Core technical skills, including experience with SAS preferred

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Information Technology Professional (IT Support)

U.S. Navy

Dallas, TX 75217

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Technical Writer - Level 3

Lockheed Martin

Fort Worth, TX 76137

~ 44 min OnsiteFlexible Schedule

3-6 years of professional technical writing experience in aerospace, defense, or a similarly regulated industry; direct exposure to joint or multi‑agency programs preferred.
Familiarity with systems engineering concepts, system architecture, and/or basic hardware/software terminology; ability to read schematics, block diagrams, and/or software code excerpts.
Bachelor's degree in Engineering, Computer Science, Technical Communication, or a related technical field.
Ability to obtain and maintain a Secret (or higher) clearance as required by the program.
This position requires a government security clearance, you must be a US Citizen for consideration.
Clearance Level: Secret

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Principal Engineer - Python API Development

Fidelity Investments

Southlake, TX 76092

~ 36 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.