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Data Engineer Ai Infrastructure

New York,NY

699 Data Engineer Ai Infrastructure jobs in New York,NY

New, Posted 5 hours ago
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Sr. Data Engineer

Subway Restaurants

Westport, CT 06880

$119,200-$149,000/yr
~ 1 hr 6 min OnsiteUrgently HiringEducation AssistanceHealth InsuranceRetirement Benefit

  • Bachelor's degree in Computer or Information Science or related field, or equivalent combination of education and experience
  • 5–8 years creating quality data pipelines and system integrations
  • At least 3 years of experience in a cloud environment
  • Hands-on experience building lakehouse solutions on Databricks (Delta Lake, Unity Catalog) or Snowflake (Iceberg Tables, Horizon Catalog)
  • Proven ability to design Bronze/Silver/Gold layers for curated, analytics-ready data
  • Experience implementing Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake Dynamic Tables / Snowpipe Streaming
  • Experience building and managing semantic models using Databricks AI/BI Genie or Unity Catalog Metrics or Snowflake Semantic Views / Cortex Analyst
  • Building pipelines with Airflow, Databricks Lakeflow, or Snowflake Openflow; familiarity with dbt is a plus
  • Strong PySpark or advanced SQL skills; Python for data engineering or automation
  • Dimensional modeling, Data Vault, or schema design for analytical workloads
  • Cluster/warehouse sizing, partitioning, clustering keys, Z-ordering, or query optimization
  • Working knowledge of Unity Catalog (Databricks) or Horizon Catalog (Snowflake) for lineage, access control, or data quality
  • Git, Databricks Asset Bundles or Snowflake CLI/Schemachange, automated testing, or deployment pipelines
  • AWS (S3, Glue, Kinesis), Azure, or GCP services supporting modern data platforms
  • Familiarity with Databricks Mosaic AI or Snowflake Cortex for GenAI or ML use cases
  • Strong communication skills to partner with Product Owners, Analysts, or cross-functional engineering teams
  • Authorized to work in the country the position is based
SmartExplore AI is experimental.
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New, Posted 1 day ago
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Lead AI Engineer (AI Foundations, LLM Core and Agentic AI)

Capital One

New York, NY 10001

New, Posted 5 hours ago
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Sr. Data Engineer

Subway Restaurants

Fairfield, CT 06824

$119,200-$149,000/yr
~ 1 hr 14 min OnsiteUrgently HiringEducation AssistanceHealth InsuranceRetirement Benefit

  • Bachelor's degree in Computer or Information Science or related field, or equivalent combination of education and experience
  • 5–8 years creating quality data pipelines and system integrations
  • At least 3 years of experience in a cloud environment
  • Hands-on experience building lakehouse solutions on Databricks (Delta Lake, Unity Catalog) or Snowflake (Iceberg Tables, Horizon Catalog)
  • Proven ability to design Bronze/Silver/Gold layers for curated, analytics-ready data
  • Experience implementing Lambda or Kappa architectures using Databricks Structured Streaming / DLT or Snowflake Dynamic Tables / Snowpipe Streaming
  • Experience building and managing semantic models using Databricks AI/BI Genie or Unity Catalog Metrics or Snowflake Semantic Views / Cortex Analyst
  • Building pipelines with Airflow, Databricks Lakeflow, or Snowflake Openflow; familiarity with dbt is a plus
  • Strong PySpark or advanced SQL skills; Python for data engineering or automation
  • Dimensional modeling, Data Vault, or schema design for analytical workloads
  • Cluster/warehouse sizing, partitioning, clustering keys, Z-ordering, or query optimization
  • Working knowledge of Unity Catalog (Databricks) or Horizon Catalog (Snowflake) for lineage, access control, or data quality
  • Git, Databricks Asset Bundles or Snowflake CLI/Schemachange, automated testing, or deployment pipelines
  • AWS (S3, Glue, Kinesis), Azure, or GCP services supporting modern data platforms
  • Familiarity with Databricks Mosaic AI or Snowflake Cortex for GenAI or ML use cases
  • Strong communication skills to partner with Product Owners, Analysts, or cross-functional engineering teams
  • Authorized to work in the country the position is based
SmartExplore AI is experimental.
View now
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IT Infrastructure Architect, Staff

Curtiss-Wright

Parsippany, NJ 07054

RemotePaid Time OffRetirement Benefit

  • 5-12 years of experience in infrastructure, systems engineering, or related roles
  • Broad experience in enterprise IT environments (not limited to a single system or tool)
  • Exposure to core infrastructure areas such as: Identity and access management (e.g., Active Directory or similar)
  • Server environments (Windows and/or Linux)
  • Application or platform support
  • Experience participating in system upgrades, migrations, or integrations
  • Demonstrated ability to learn and adapt to new technologies quickly
  • Strong communication and interpersonal skills
  • Proven ability to produce clear documentation with attention to detail
  • Exposure to Microsoft environments (Active Directory, Windows Server, SQL Server, Exchange) preferred
  • Experience with virtualization (e.g., VMware) preferred
  • Familiarity with cloud platforms (e.g., Azure) preferred
  • Exposure to CMDB or service management tools preferred
  • Experience working alongside ERP or business systems teams preferred
  • Any experience with platform ownership or application support preferred
SmartExplore AI is experimental.
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Principal Engineer - Python API Development

Fidelity Investments

Secaucus, NJ 07094

~ 18 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
New, Posted 20 hours ago
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Vice President, Product Design

BNY

New York, NY 10007

New, Posted 1 day ago
Recommended
Software Engineer II - Infrastructure

Disney Entertainment and ESPN Product & Technology Careers

New York, NY 10025

$117,500-$157,500/yr
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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.
View now
New, Posted 11 hours ago
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Associate, Infrastructure Project Advisory (Construction/Engineering)

KPMG

New York, NY 10025

OnsiteHealth InsuranceRetirement Benefit

  • Minimum one year of recent experience in field construction management or construction advisory services with increasing roles and responsibilities in a variety of large capital project types for both public and private clients
  • Bachelor's degree or masters' degree in Engineering, Architecture, Building Science, Construction Management, or a related field from an accredited college or university
  • Professional Engineer, Project Management, Certified Construction Manager, Certified Public Accountant, American Institute of Architects, or other professional certification is preferred
  • Demonstrated client coordination and subcontractor management for full life cycle construction projects including planning and work breakdown structures, pre-construction services, sourcing and procurement of contracts, contract administration, scheduling, cost estimating, quality management, project reporting, and project closeout
  • Experience using various project management tools such as Procore, E-Builder, Primavera, Enterprise, Prolog, and other toolsets
  • Excellent written and verbal communication, documentation, records retention, and work paper organizational skills
  • Willingness and ability to travel
  • 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.
View now
New, Posted 1 day ago
Recommended
Senior Software Engineer - Build Tooling Infrastructure

Disney Entertainment and ESPN Product & Technology Careers

New York, NY 10025

$141,900-$190,300/yr

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