660 Associate Data Governance Engineer jobs in New York,NY

Sr Dir, Business Operations and Data Governance – Intelligence Ventures

Spectrum

New York, NY 10036

OnsiteUrgently Hiring

Bachelor's Degree in Business, Finance, Operations, a related field, or equivalent practical experience
10+ Years Business operations, chief-of-staff, strategy-and-operations, or comparable leadership experience
5 years Experience owning budgets and managing cross-functional initiatives or programs
Proven experience running business operations, chief-of-staff, or strategy-and-operations functions for a senior executive or business unit, ideally in a data, technology, media, or platform business
Demonstrated ability to own a budget and partner effectively with Finance, Legal, and Compliance functions — translating between operational reality and enterprise control requirements
Experience standing up or running operational processes in a governance, compliance, privacy-operations, or data-management context — enough fluency to coordinate credibly with Privacy, Legal, and technical teams; deep data-governance subject-matter expertise is a plus, not a prerequisite, as this role operationalizes governance rather than authoring its policy
Strong cross-functional coordination skills, with a track record of defining ways of working and operating cadences across multiple stakeholder organizations and driving alignment without direct authority
Excellent program- and project-management discipline; able to manage a portfolio of concurrent initiatives, keep many workstreams on track, and bring structure to ambiguity
Sound judgment, discretion, and executive presence; trusted to represent leadership, handle sensitive information, and make or escalate decisions appropriately
Strong written and verbal communication skills, with the ability to prepare executive-level materials and facilitate leadership forums
Comfort operating in an ambiguous, early-stage, build-from-scratch environment while delivering against aggressive milestones
Working understanding of the privacy and regulatory landscape governing consumer data is a plus, sufficient to partner credibly with Privacy and Legal

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New, Posted 14 hours 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

OnsiteHealth 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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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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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

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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

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Senior Vice President, Infrastructure Engineer

BNY

Jersey City, NJ 07306

New, Posted 2 hours ago

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Lead AI Engineer (AI Foundations, LLM Core and Agentic AI)

Capital One

New York, NY 10001

New, Posted 1 day ago

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Senior Full Stack Engineer (Angular and Python)

Fidelity Investments

Jersey City, NJ 07311

~ 22 min OnsiteEducation AssistanceHealth InsurancePaid Time OffRetirement Benefit

5 plus years full stack development with Angular (TypeScript, RxJS) on the front-end
Python (pandas, NumPy) on the back-end
Strong object-oriented design
REST API fundamentals
Experience designing and building distributed data applications and pipelines at scale
Working knowledge of relational and analytical databases, specifically Oracle and Snowflake, including complex SQL
Hands-on CI/CD experience using Jenkins or comparable tools, with solid unit, integration, and end-to-end testing practices (pytest, Jasmine/Karma)
Proficiency with Git-based workflows, code review standards, and Agile/Scrum delivery
Consistent track record of designing and implementing end-to-end data systems (full stack development) from concept to launch

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