990 Data Engineer jobs in Flushing,NY

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 18 hours ago

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DiversityJobs

Data Engineer - Production Support

Gartner

Stamford, CT 06902

New, Posted 19 hours ago

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Lead Software Engineer - Data Streaming/Integration Platforms

Disney Entertainment and ESPN Product & Technology Careers

New York, NY 10025

$155,700-$208,700/yr

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Principal Engineer - Python API Development

Fidelity Investments

North Bergen, NJ 07047

~ 32 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

iHire

Senior Manager, Machine Learning Engineering

Capital One

New York, NY 10001

New, Posted 2 hours ago

Backend Engineer (C# / .NET Healthcare Technology)

LI Script

Woodbury, NY 11797

New, Posted 18 hours ago

DiversityJobs

Sr Engineer Site Reliability

Optimum Communications

Bethpage, NY 11714

$100,246-$143,208/yr

New, Posted 5 hours ago

AI Engineering Delivery Lead (Beta Launch)

Digital Culture LLC

New York, NY 10025

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89% of jobs ask for a resume

Don't let the perfect job slip away—upload your resume and we'll personalize your results instantly.

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Quality Inspector

Ametek

Montvale, NJ 07645

~ 48 min Onsite

High school graduate
3-5 Years mechanical inspection, manufacturing experience
Experience in basic and advanced inspection techniques using various inspection tools and methodologies
Ability to read and interpret engineering drawings using geometric dimensioning and tolerances including and understanding of maximum material conditions
Strong understanding of GD&T;
Inspect detail parts per drawing requirement and specs using industry-standard measuring equipment
Prepare and maintain inspection reports
Program and/or operate Coordinate Measuring Machines
Perform small hand tool calibration
Collect and tabulate data for SPC use

SmartExplore AI is experimental.