581 Data Engineer For Data Management jobs in Newark,NJ

Senior Associate, Data Engineer - Databricks

KPMG

New York, NY 10025

~ 30 min OnsiteHealth InsuranceRetirement Benefit

Minimum three years of recent experience as a cloud data lake/warehouse architect, designer, developer, data scientist, or AI / ML engineer
Preferably Databricks certified
Bachelor's degree in Engineering, Information Technology, Computer Science or a related field from an accredited college/university
Experience in leading projects relating to cloud modernization, data migration, data warehousing experience with cloud-based data platforms (Databricks) and experience with (preferably driving) technical workshops with technical and business clients to derive value added services and implementations
Hands-on working knowledge of topics such as data security, messaging patterns, ELT, Data wrangling and cloud computing and proficiency in data integration/EAI and DB technologies, sophisticated analytics tools, programming languages or visualization platforms
Experience designing solutions on cloud infrastructure and services, such as AWS, Azure, or GCP
Hands-on technical experience with SQL and Apache Spark
Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future and travel as needed

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Principal Engineer - Python API Development

Fidelity Investments

Harrison, NJ 07029

~ 7 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

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Business Development Manager, STEM Partnerships

Liberty Science Center

Jersey City, NJ 07305

~ 20 min OnsiteHealth InsurancePaid Time OffRetirement Benefit

Valid driver's license (required)
8 hours per day, Monday through Friday, with flexibility for evenings and weekends as needed to meet business requirements
Travel to partner sites and conferences will be required
Ability to drive is a requirement
Travel to conferences, meetings, and partner sites to observe off-site programming will be required

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Senior Technologist, Data Center Fluids

Wayne, NJ 07470

Hybrid~ 29 minFlexible ScheduleHealth InsuranceRetirement Benefit

Degree in Chemistry, Engineering, or related technical discipline.
Up to 25% travel should be expected with this role
This may include pre-placement drug screening, medical review of physical fitness for the role, and background checks.

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New, Posted 1 day ago

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Sr Product Manager II, Data Product Management

Disney Entertainment and ESPN Product & Technology Careers

New York, NY 10025

$163,100-$218,700/yr

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New Product Manufacturing Engineer

CACI International Inc

Florham Park, NJ 07932

~ 30 min Onsite

Ability to work independently with minimal supervision and mentor lower-level professionals.
Must be a US person.
BA/BS degree in a technical discipline from an accredited college or university.
Minimum of five (5) years of experience as a manufacturing engineer or in a related role.
Percentage of Travel Required: Up to 10%
Type of Travel: Local

SmartExplore AI is experimental.

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Principal Engineer - Python API Development

Fidelity Investments

Newark, NJ 07175

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

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 11 hours ago

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Manager, Economic Services - Data Science

KPMG

New York, NY 10025

~ 30 min OnsiteHealth InsuranceRetirement Benefit

Minimum of five years of recent experience with advisory related projects within a quantitative analysis firm, consulting firm, or background in a scientific laboratory
PhD in the areas of Computer Science, Mathematics, Mathematical Statistics, Electrical Engineering is required
A portfolio of projects (such as via GitHub, personal website, or other platforms) that demonstrates expertise in building and deploying AI/ML models and NLP solutions
Experience building data science or LLM-based products, with a demonstrable track record of your personal contributions to the codebase
Demonstrated experience in the development, application and interpretation of complex economic and statistical modeling frameworks using Python or R
Applicants must be authorized to work in the US without the need for employment-based visa sponsorship now or in the future; KPMG LLP will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa)

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Senior Buyer Planner, Procurement

PNY Technologies

Parsippany, NJ 07054

~ 25 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

8+ years of combined experience in procurement, buyer/planner, materials planning, supply planning, supply chain operations, or related roles.
Hands-on experience with ERP/MRP systems, purchase order management, RFQs, supplier coordination, inventory analysis, and production or materials planning.
Proven experience managing suppliers and/or contract manufacturers, including delivery performance, pricing, lead times, quality, and issue resolution.
Advanced Microsoft Excel skills required; experience with Word, Outlook, and PowerPoint required.
Bachelor's degree in Business, Supply Chain, Operations, or a related field preferred; equivalent experience will also be considered.
Power BI experience is a plus.
Experience working in a manufacturing, technology, electronics, hardware, consumer products, or contract manufacturing environment strongly preferred.
Familiarity with consignment inventory and VMI models preferred.

SmartExplore AI is experimental.