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Data Engineer Consultant

Harrison,NJ

734 Data Engineer Consultant jobs in Harrison,NJ

New, Posted 1 day ago
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Senior Vice President, Forward Deployed Engineer

BNY

New York, NY 10007

$104,000-$210,000/yr
Urgently Hiring
New, Posted 23 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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New Product Manufacturing Engineer

CACI International Inc

Florham Park, NJ 07932

~ 29 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

~ 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.
View now
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Estimator

Specialized Fire & Security

Riverdale, NJ 07457

~ 38 min Onsite

  • Minimum of 5 years experience in estimating low voltage systems
  • The ability to read architectural and engineering drawings and prints
  • Proficient in Bluebeam (REVU), Microsoft Excel & Microsoft Access
  • Ability to work independently and in team environment
  • Must be legally authorized to live within the USA
  • Must be legally authorized to work in the USA
  • Must be a legal citizen of the USA
  • Fluent in English
SmartExplore AI is experimental.
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Director of Engineering

Marine Electric Systems

South Hackensack, NJ 07606

~ 21 min OnsiteHealth InsurancePaid Time OffRetirement Benefit

  • 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.
SmartExplore AI is experimental.
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New, Posted 5 hours ago
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Senior Associate, Revenue Cycle Consultant

KPMG

New York, NY 10025

~ 25 min OnsiteHealth InsuranceRetirement Benefit

  • Minimum three years of consulting experience focused on revenue cycle operational or financial improvement, systems integration, or equivalent industry experience
  • Minimum one year of direct supervisory experience preferred
  • Bachelor's degree from an accredited college / university
  • Must have two years of analytics experience with handling, analyzing and evaluating large data sets using at least one of the following tools: Microsoft Excel, Tableau, Power BI, SQL, Alteryx, and/or Data Warehouse management
  • If an Epic recruit, experience with the following Epic modules such as Resolute (Hospital/Physician), Cadence, Prelude/ADT and Reporting Workbench
  • Progressive experience implementing operational improvement plan(s) across the healthcare revenue cycle including financial clearance, scheduling, referral management, billing, follow-up/collections, and vendor management
  • Proficiency with foundational consulting skills such as analytical, written and verbal communications, appropriate client presence, facilitation, and presentation abilities
  • Solid understanding of revenue cycle concepts including financial clearance, insurance verification, financial counseling, patient estimations, registration functions, referral management, operational & financial metrics, industry leading practices, and key revenue cycle key performance indicators
  • Ability to travel up to 50%
  • Must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future
SmartExplore AI is experimental.
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New, Posted 6 hours ago
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Head of Technology, Intelligence Ventures

Spectrum

New York, NY 10036

~ 25 min Onsite

  • Deep expertise across the full intelligence platform stack — including distributed data pipelines, ML platform architecture, embedding systems, feature stores, agent-to-agent API design, and LLM-powered application layers — with demonstrated ability to architect and ship all layers as a coherent, production-grade product
  • Demonstrated experience architecting and operating consumer data intelligence or data product platforms underpinned by complex machine learning systems and built on modern, cloud-native data infrastructure
  • Hands-on proficiency with Snowflake (including Cortex, Native Apps, and data sharing frameworks), cloud data platforms (AWS, Azure, or GCP), and production ML/AI systems at scale
  • Experience building agentic AI systems and LLM-powered product interfaces — including agent-to-agent APIs, retrieval-augmented generation architectures, and natural language UIs grounded in proprietary data — with strong product instincts around accuracy, trust, and user experience for non-technical enterprise audiences
  • Proven ability to translate complex technical architecture into clear executive and partner-facing communications; comfortable engaging at the C-suite level and in strategic partner negotiations with hyperscalers and technology platforms
  • Strong understanding of privacy-preserving data architecture, including differential privacy, de-identification techniques, zero-copy and clean room frameworks, and the regulatory landscape governing consumer behavioral data
  • Track record of recruiting and developing exceptional engineering talent in competitive markets; experience building high-performance teams from early-stage through scaled operations
  • Experience managing external development partners and outsourced engineering resources alongside an internal team in a fast-moving, build-from-scratch environment
  • Ability to operate in an ambiguous, early-stage environment while maintaining rigorous engineering standards and delivering against aggressive milestones
  • Experience building externally-consumed data or intelligence platforms — including developer-facing APIs, data marketplace integrations, or partner-accessible data products — with strong instincts around developer experience, access governance, and commercial platform design
  • Bachelor's Degree in Computer Science, Software Engineering, Electrical Engineering, or a related technical field
  • Experience leading consumer data intelligence, AI/ML platform, or data product engineering organizations — 10 years
  • Engineering leadership and team-building experience, including managing senior technical staff — 7 years
SmartExplore AI is experimental.
View now
New, Posted 23 hours ago
Recommended
Senior Consultant, Healthcare Strategy & Transformation

Guidehouse Careers

New York, NY 10025

Apply Directly
Principal Engineer - Python API Development

Fidelity Investments

Harrison, NJ 07029

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.
View now

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