717 Data Engineer Java Aws jobs in New York,NY

~ 22 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Principal Engineer - Python API Development

Fidelity Investments

Jersey City, NJ 07311

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.

Senior Software Developer - AWS / Platform

Disney Entertainment and ESPN Product & Technology Careers

New York, NY 10025

$141,900-$190,300/yr

Lead Software Engineer - Data Streaming/Integration Platforms

Disney Entertainment and ESPN Product & Technology Careers

New York, NY 10025

$155,700-$208,700/yr

~ 16 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Principal Engineer - Python API Development

Fidelity Investments

Hoboken, NJ 07030

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.

Quality Inspector

Ametek

Garden City, NY 11530

~ 40 min Onsite

Hours: Monday-Friday 07:00AM-03:30PM
Read and interpret aerospace engineering drawings using geometric dimensioning and tolerances including and understanding of maximum material conditions
Inspect detail parts and assemblies per drawing requirement and specs using standard measuring equipment
Program and/or operate Coordinate Measuring Machine
Perform Hardness testing
Collect and tabulate data for SPC use
Review Supplier F.A.I.R./Generate First Article Reports per AS9102
Basic computer knowledge including MS Excel and Word
Interpret drawing requirements/specs and geometric dimensions and tolerances
Familiar with MIL, NAS, MS, AMS, AWS and AS specifications and standards
PCDMIS programming skills
Familiar with special process specifications for heat treat, welding, and non-destructive testing
High school graduate
3-5 Years mechanical inspection, aerospace experience
Please note, all Production Floor employees are required to wear steel toe boots.
Due to the nature of AMETEK Hughes-Treitler's programs and products, applicants must have the legal right to work in the US and additionally must be legally authorized to access export-controlled information and source code.
Nearest Major Market: Long Island
Nearest Secondary Market: New York City

Lead AI Engineer (AI Foundations, LLM Core and Agentic AI)

Capital One

New York, NY 10001

~ 26 min OnsiteHealth InsurancePaid Time OffRetirement Benefit

Director of Engineering

Marine Electric Systems

South Hackensack, NJ 07606

Bachelor's degree in Electrical Engineering or a closely related engineering discipline.
Significant experience in electrical engineering, sustaining engineering, production engineering, test engineering, or engineering leadership in a manufacturing environment.
Strong hands-on technical knowledge of electrical and electromechanical systems.
Experience with PCB troubleshooting, electrical testing, components, assemblies, and production support.
Ability to read and interpret drawings, schematics, specifications, technical data packages, and test procedures.
Experience supporting manufacturing, production, repair, or sustainment work.
Ability to make practical engineering decisions with imperfect information.
Strong communication skills and ability to work cross-functionally with production, quality, procurement, sales, and leadership.
Demonstrated ability to mentor junior engineers or technical staff.
Strong organizational skills and ability to create structure in a fast-moving small-company environment.

~ 30 min OnsiteBilingual PreferredEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Chief Systems Engineer

L3 Harris

Clifton, NJ 07011

Bachelor's Degree with a minimum of 12 years of prior related experience.
Graduate Degree with a minimum of 10 years of prior related experience.
In lieu of a degree, minimum of 16 years of prior related experience.
2 years of experience in Cameo and SysML v1
3 years experience with Agile development and using JIRA
Active Secret Security Clearance- Ability to obtain and maintain any additional clearances as required.

ResumeLibrary

PolyPath Market Risk Specialist

Santander Holdings USA

New York, NY 10022

Onsite

Bachelor's Degree: in related field or equivalent demonstrated through a combination of work experience, training, military service, or education - Required
Expert-level knowledge of PolyPath
Strong experience in market risk, preferably within banking or capital markets
Strong programming skills in Python and Java
Solid understanding of fixed income products, pricing, valuation, and risk analytics
Experience supporting risk models, valuation tools, pricing engines, or market risk platforms
Ability to troubleshoot complex system, data, and pricing issues across multiple technology platforms
Strong analytical skills with the ability to explain technical and market risk concepts clearly to both business and technology teams
Experience working in a large banking, financial services, or regulated financial institution environment
10+ years of experience in banking, capital markets, financial technology, or market risk technology preferred
Work authorization to be legally authorized to work in the United States on a full-time basis without requiring employer sponsorship to commence employment

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