742 Hpc Data Storage Engineer jobs in New York,NY

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.

SmartExplore AI is experimental.

Apply Directly

Manufacturing Engineer- Westbury, NY

Hubbell Incorporated

Westbury, NY 11590

$105,000-$120,000/yr

~ 40 min Onsite

Bachelor's degree in manufacturing engineering/Mechanical Engineering or similar technical area.
3-5 years' Experience in an electronics manufacturing environment where electrical testing of Printed Circuit boards and/or finished goods is performed

SmartExplore AI is experimental.

New, Posted just now

Recommended

Easy Apply

Human Resources Technology Data Engineer

LHH US

New York, NY 10025

$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.

New, Posted 1 day ago

Recommended

Apply Directly

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 21 hours ago

Apply Directly

Senior Vice President, Infrastructure Engineer

BNY

Jersey City, NJ 07306

New, Posted just now

Apply Directly

Head of Technology, Intelligence Ventures

Spectrum

New York, NY 10036

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.

Apply Directly

Head of AlphaGen - Investor Research Product Engineering, Director

Blackrock

New York, NY 10025

OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's degree in Computer Science, Engineering, or a related field; or equivalent practical experience
An advanced degree is a plus
Strategic Engineering Leadership: Proven experience leading large-scale engineering organizations through product transformation initiatives (e.g., platform modernization, cloud migration, operating model changes). Demonstrated success in setting vision and executing across complex, multi-year technology programs
Alpha generation workflows or closely related quantitative research processes in finance/investments
Cloud technologies and cloud-native architectural patterns (e.g., microservices, containerization, distributed computing e.g. Ray)
API-first platform design and developer experience best practices
AI/ML applications for workflow automation, data validation, and operational excellence
Modern stack knowledge and skills - e.g. Python, Polars, Ray, MLFlow or equivalent technology
Demonstrated strength in partnership-building and cross-functional collaboration
Able to influence and align product teams, platform/infrastructure teams, and governance bodies around a common vision and roadmap
Ability to operate in complex market and organizational contexts, translating strategic objectives into actionable plans
Proven track record of driving innovation, navigating ambiguity, and delivering measurable outcomes at scale
AI-First, Human-in-the-Loop: Embraces AI-driven solutions as a default for efficiency and scale, while keeping expert human judgment in critical loops to ensure quality and trust
Platform Over People: Prioritizes building robust platforms and automation over relying on individual heroic efforts, enabling sustainable and scalable growth
Single Front Door: Advocates for a unified user experience where researchers and stakeholders have one intuitive portal for all their needs, simplifying access and support
Standardization Everywhere: Drives consistency in tools, processes, and data across the board, reducing complexity and improving interoperability and maintainability
Self-Service as the Default: Champions self-service capabilities, empowering users to accomplish tasks independently (from data ingestion to model deployment) without bespoke engineering work
Deep Co-Ownership with PMG: Fosters a culture of partnership with the Portfolio Management Group, aligning closely on priorities, sharing roadmaps and KPIs, and co-owning outcomes to ensure the platform truly meets investment teams' needs
For New York, NY Only the salary range for this position is USD$225,000.00 - USD$285,000.00
Additionally, employees are eligible for an annual discretionary bonus, and benefits including healthcare, leave benefits, and retirement benefits
BlackRock operates a pay-for-performance compensation philosophy and your total compensation may vary based on role, location, and firm, department and individual performance
4 days in the office per week, with the flexibility to work from home 1 day a week

SmartExplore AI is experimental.

New, Posted just now

Apply Directly

Head of AI Data Science, Intelligence Ventures

Spectrum

New York, NY 10036

Onsite

Deep expertise in transformer-based sequence modeling and its application to behavioral or interaction data at consumer scale — including architecture design, training methodology, fine-tuning, and embedding quality evaluation
Proven track record developing and deploying household- or user-level embedding models applied to real-world use cases in media, marketing, commerce, and/or customer intelligence — not just research environments. Demonstrated understanding of the unique characteristics of behavioral sequence data: sparsity, temporal dynamics, multi-entity structure, and the signal differences between behavioral intent and explicit interaction
Strong command of the full data science lifecycle in production settings — from exploratory data analysis and feature engineering through model training, validation, deployment, monitoring, and iteration — at large dataset scale (billions, even trillions of records)
Hands-on proficiency with Python, PyTorch or TensorFlow, and distributed ML training frameworks; experience running ML workloads on cloud platforms (AWS SageMaker, Snowflake Cortex, Databricks, or equivalent)
Experience designing and operationalizing feature stores and predictive modeling pipelines that serve downstream intelligence products, audiences, or decision systems in production environments
Ability to communicate complex AI/ML concepts clearly to non-technical executive audiences, product stakeholders, and external partners; comfort operating as an external-facing technical spokesperson for the platform's modeling capabilities and intelligence differentiation
Track record of leading and growing high-performing data science teams; experience recruiting and developing senior ML talent in competitive markets
Genuine intellectual curiosity about the application of AI to behavioral science, consumer intelligence, and agentic systems; awareness of the evolving landscape of foundation models, retrieval-augmented generation, and multi-agent AI architectures
Bachelor's Degree in Computer Science, Statistics, Mathematics, or a related quantitative field
Experience leading applied ML or data science teams building consumer-facing or enterprise intelligence products — 7 years
Hands-on experience designing and training transformer or deep learning models on sequential behavioral data at scale — 5 years
In-office position preferably based in New York City
Travel as required for partner engagements, executive meetings, and industry events

SmartExplore AI is experimental.

Apply Directly

New Product Manufacturing Engineer

CACI International Inc

Florham Park, NJ 07932

~ 50 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.

Recommended

Apply Directly

Director, Software Engineering (Electronic Trading)

Fidelity Investments

Belleville, NJ 07109

~ 27 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

Bachelor's degree in Computer Science, Engineering, Information Technology, or equivalent.
15+ years of hands-on software design and development experience in the electronic trading domain.
5+ years of technical leadership, managing a team, and mentoring software developers
Experience in building **algorithmic trading** systems for **equities and options**
Experience with**equities and options market data**
Expertise in **C/C++** , **Python** , and **Linux**.
Deep experience with **low latency messaging systems** (e.g., 29West/Ultra-Messaging, Kafka).
Proficiency in **KDB+** or other time-series databases.
Strong background in building **scalable** , **distributed** , **asynchronous** , and **event-driven** applications.
Advanced knowledge of **low latency design patterns** and **performance optimization** techniques.
Experience in **Capital Markets** or **Brokerage systems** , especially **order management**.
Solid understanding of the **FIX protocol** and FIX engines.
Experienced with using **GenAI developer assist tools** (e.g. GitHub Copilot).
Experience with **CI/CD tools** such as GitHub, Maven, Jenkins, Artifactory, and uDeploy.
Experience with deploying applications and services in **AWS**