813 Data Engineer Python Sql And Airflow jobs in New York,NY

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Principal Engineer - Python API Development

Fidelity Investments

Jersey City, NJ 07311

~ 22 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.

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New, Posted 1 day ago

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Human Resources Technology Data Engineer

LHH US

Sunnyside, NY 11104

$85-$100/hr

Hybrid~ 10 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.

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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.

SmartExplore AI is experimental.

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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.

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

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Associate or Senior Associate, Fixed Assets / Cost Segregation Engineer (AMCS)

KPMG

New York, NY 10025

OnsiteUrgently HiringHealth InsuranceRetirement Benefit

Bachelor's degree from an accredited college/university in engineering, architecture, construction management, or a closely related discipline is required
Minimumone year of recent experience in an engineering firm, corporation, or public accounting firm; background in cost segregation, fixed asset consulting, construction, engineering, or a related technical field is preferred
Understanding of construction processes and building systems, and how project costs translate into asset classifications
Basic knowledge of federal income tax depreciation principles and accounting for capital expenditures, or a demonstrated interest in developing this skillset
Experience reviewing technical drawings, construction documentation, or large project cost datasets
Strong proficiency in Excel (such as advanced formulas, pivot tables, lookups) and experience working with structured data from financial or operational systems; demonstrated experience or strong aptitude with data-wrangling/automation tools (such as Power Query, Alteryx), business intelligence tools (such as Power BI, Tableau), or query/scripting languages (such as SQL, Python, R)
Applicant must be authorized to work in the U.S. 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 is available 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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Manufacturing Engineering Manager - Boonton, NJ

Hubbell Incorporated

Boonton, NJ 07005

~ 49 min Onsite

BS in Electrical, Industrial, Mechanical Engineering or similar
5+ years experience in an Electronics, Electro-Mechanical, or relevant manufacturing environment
Proven track record for handling new product launches through PFMEA assembly line creation, ERP setup work etc.
Proven track record of conceptualizing and implementing Test automation framework on the manufacturing floor to reduce takt times and improve process quality,
Must be fluent with mechanical 3D CAD package.
Must be able to read schematics to troubleshoot board level issues
Experience with Electronics and manufacturing of Printed Circuit Board (PCB) Assemblies.
Must possess excellent verbal and written communications skills
An understanding of lean tools and concepts is essential, i.e. time studies, kaizen events, Value Stream Maps, etc
A continuous improvement mindset is critical
Must be familiar with ISO 9000

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Head of Technology, Intelligence Ventures

Spectrum

New York, NY 10036

OnsiteUrgently Hiring

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

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New, Posted 2 hours ago

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Senior Associate, Data Engineer - Databricks

KPMG

New York, NY 10025

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

SmartExplore AI is experimental.

New, Posted 1 day ago

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