644 Data Engineer Etl Development jobs in New York,NY

Senior AWS Redshift Data Engineer (Contract | 1099)

BrainTrust

New York, NY 10001

New, Posted 1 day ago

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Human Resources Technology Data Engineer

LHH US

New York, NY 10022

$85-$100/hr

HybridHealth InsurancePaid Time OffRetirement Benefit

Bachelor's degree in Computer Science, Engineering, or a related field.
5-8 years of professional software engineering experience.
Proven track record of hands on development in enterprise scale systems, preferably in HR.
Strong proficiency in at least one core programming language (Python or Java).
Deep experience with relational databases, NoSQL stores, and complex query design.
Experience working with HR, people operations, or workforce analytics data, including sensitive data handling, HRIS integrations (e.g., Dayforce, Culture Amp, etc.), and secure data exchange patterns.
Demonstrated ability to build or support platforms involving employee lifecycle data, compensation structures, organizational hierarchies, and talent management workflows.

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Principal Engineer - Python API Development

Fidelity Investments

Harrison, NJ 07029

~ 23 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.

Recommended

Apply Directly

Principal Engineer - Python API Development

Fidelity Investments

Hoboken, NJ 07030

~ 16 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.

Recommended

Easy Apply

Human Resources Technology Data Engineer

LHH US

Astoria, NY 11106

$85-$100/hr

Hybrid~ 12 minHealth InsurancePaid Time OffRetirement Benefit

Bachelor's degree in Computer Science, Engineering, or a related field.
5-8 years of professional software engineering experience.
Proven track record of hands on development in enterprise scale systems, preferably in HR.
Strong proficiency in at least one core programming language (Python or Java).
Deep experience with relational databases, NoSQL stores, and complex query design.
Experience working with HR, people operations, or workforce analytics data, including sensitive data handling, HRIS integrations (e.g., Dayforce, Culture Amp, etc.), and secure data exchange patterns.
Demonstrated ability to build or support platforms involving employee lifecycle data, compensation structures, organizational hierarchies, and talent management workflows.

SmartExplore AI is experimental.

New, Posted 1 day ago

Recommended

Lead Software Engineer - Data Streaming/Integration Platforms

Disney Entertainment and ESPN Product & Technology Careers

New York, NY 10025

$155,700-$208,700/yr

New, Posted 1 day ago

DiversityJobs

Software Engineering/Applications Leadership Advisory - Executive Technology Services for Global Enterprises

Gartner

Newark, NJ 07175

New, Posted 1 day ago

Senior Consultant, Healthcare Strategy & Transformation

Guidehouse Careers

New York, NY 10025

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Manufacturing Engineer- Westbury, NY

Hubbell Incorporated

Westbury, NY 11590

$105,000-$120,000/yr

~ 40 min Onsite

Bachelor's degree in manufacturing engineering/Mechanical Engineering or similar technical area.
3-5 years' Experience in an electronics manufacturing environment where electrical testing of Printed Circuit boards and/or finished goods is performed

SmartExplore AI is experimental.

New, Posted 1 day ago

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