Senior Analytics Engineer Salary India in New York

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for. About the Role, Mission or Department Overview We are looking for a Senior Program Manager to shape and lead our People Data & Insights team by turning complex HR questions into scalable, automated solutions. In this high-visibility role, you will partner directly with HR leadership to create our roadmap while managing the end-to-end lifecycle from intake to delivery. You will spend equal time translating business needs with stakeholders and partnering with engineers on technical execution. Beyond building tools, you will own the critical final mile by driving adoption and ensuring leaders understand and trust the insights we deliver. You will report to our Senior Director, People Data & Insights. Responsibilities: You will handle sensitive people data and own the roadmap for people data solutions, from intake through launch, and adoption You will oversee request intake and the prioritization process ensuring requesters understand what is being built, what is not, and why You will translate business questions into solution requirements You will partner daily with the Analytics Engineer and Solutions Architect on scoping, sequencing, and delivery You will build the education layer into the solution itself. You will partner on data governance, contribute to the data dictionary, and hold the line on metric definitions You will manage stakeholders across HR, Technology, Legal, and the business, including senior leaders. You will demonstr

The mission of The New York Times is to seek the truth and help people understand the world. That means independent journalism is at the heart of all we do as a company. It’s why we have a world-renowned newsroom that sends journalists to report on the ground from nearly 160 countries. It’s why we focus deeply on how our readers will experience our journalism, from print to audio to a world-class digital and app destination. And it’s why our business strategy centers on making journalism so good that it’s worth paying for. About the Role, Mission or Department Overview As a Senior Engineer, Marketing, you'll be embedded with the Marketing team, providing us with technical leadership, consulting, and systems thinking. You'll assemble the orchestration systems, integrations, and AI capabilities that help teams work faster, and in more data‑driven ways. You will lead end‑to‑end design, implementation, and management of the marketing campaign lifecycle system, integrations, internal tools, and learning/experimentation infrastructure. You will report to our Director, Advertising Systems. Responsibilities: You will write high-quality, secure, and well-tested code, contributing to standards and documentation for Marketing infrastructure, data models, and tools You will build the campaign lifecycle orchestration backbone You will build integrations and internal tools that connect project management, collaboration, creative, media, and email/lifecycle platforms You will work with Marketing partners as a technical advisor, translating needs into designs You will integrate AI agents and automations (including LLM-powered flows) into Marketing workflows according to company GenAI guidance You will design and operate data pipelines and models that ingest marketing and performance data into a data layer, supporting experimentation and analytics workflows You will deliver abstractions and APIs that ensure AI systems and our users to create campaign wrap-ups, insights, next-t

We believe that the way people interact with their finances will drastically improve in the next few years. We’re dedicated to empowering this transformation by building the tools and experiences that thousands of developers use to create their own products. Plaid powers the tools millions of people rely on to live a healthier financial life. We work with thousands of companies like Venmo, SoFi, several of the Fortune 500, and many of the largest banks to make it easy for people to connect their financial accounts to the apps and services they want to use. Plaid’s network covers 12,000 financial institutions across the US, Canada, UK and Europe. Founded in 2013, the company is headquartered in San Francisco with offices in New York, Seattle, Washington D.C., Raleigh, London, and Amsterdam. Making data-driven decisions is key to Plaid's culture. To support that, we need to scale our data systems while maintaining correct and complete data. We provide golden datasets and tooling to teams across engineering, product, and business and help them explore our data quickly and safely to get the data insights they need, which ultimately helps Plaid serve our customers more effectively. In addition, Plaid will not be successful if we can't move quickly. We build the data systems and tools that enable everyone at Plaid to be data-driven, making analytics easy, obvious, and proactive across the company. Data Engineers heavily leverage SQL and Python to build data workflows that integrate with our Golang applications. We use tools like DBT, Airflow, Redshift, Atlan, and Retool to orchestrate data pipelines and define workflows. We work with engineers, product managers, business intelligence, data analysts, and many other teams to build Plaid's data strategy and a data-first mindset. You will be in a high impact role that will directly enable business leaders to make faster and more informed business judgements based on the datasets you build. You will have the opportunity to car

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. We are looking for a Senior Solution Engineer who thrives at the intersection of data, AI, and complex enterprise architecture. In this role you will work directly with the sales team and channel partners to understand the data challenges of our customers, strategize on how to navigate winning sales cycles, deliver compelling data-driven demonstrations, and support enterprise Proof of Concepts that showcase measurable business outcomes. As a Snowflake Solution Engineer you must share our passion for transforming how organizations use data — from raw ingestion to real-time analytics to AI-powered applications. You thrive in a dynamic environment, are equally comfortable whiteboarding a medallion architecture with a data engineering team and presenting data ROI to a C-suite, and you bring deep opinions about what good data platform design looks like. IN THIS ROLE YOU WILL GET TO: Present Snowflake's Data Cloud vision to data engineering leaders, analytics teams, data scientists, and executive stakeholders at prospects and customers Lead hands-on technical discovery to map a customer's existing data architecture — pipelines, warehouses, lakehouses, governance gaps — and design a Snowflake-native path forward Build and deliver tailored demos and proof of concepts across Snowfla

We are investing in agentic AI and need a Senior AI Engineer to lead the design and delivery of these systems. This is a foundational hire: you will own both the agent-facing workstreams — pipelines, orchestration, conversational interfaces — and the underlying context layer that makes them reliable, including memory management, knowledge graph integration, and retrieval infrastructure. You will work closely with data engineers, project leads, and client stakeholders, and play a key role in shaping how Lynx builds and ships AI solutions at scale. What This Involves: Lead the architecture and delivery of agentic AI systems end-to-end: agents, orchestration, tool use, and multi-step reasoning workflows. Own the context layer: design and implement memory architectures (episodic, semantic, working memory) and integrate GraphRAG and knowledge graph retrieval into agentic pipelines. Build robust RAG systems — including vector retrieval, graph traversal, and hybrid search — and ensure retrieval quality through evaluation frameworks. Translate client requirements into technical designs, presenting approaches and trade-offs to both technical and non-technical stakeholders. Define standards and reusable patterns for agentic AI development that other engineers at Lynx can build on. Set up observability, evaluation, and monitoring pipelines to ensure AI systems perform correctly in production. Requirements: 5–8 years of software or ML engineering experience, with at least 2–3 years building LLM-based or agentic AI systems in production. Deep hands-on experience with agentic frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, or similar) and LLM APIs (OpenAI, Anthropic, etc.). Strong understanding of agent design patterns: ReAct, planning loops, tool use, multi-agent coordination, and memory architectures. Practical experience with GraphRAG or knowledge graph-based retrieval (e.g., Neo4j, Microsoft GraphRAG) and vector databases (Pinecone, Weaviate, Qdrant, etc.). Proficiency in

SUMMARY STATEMENT We are looking for a Solution Architect to design the technical solutions behind our client engagements and give delivery teams a clear, workable path from concept to production. You will work across enterprise data, software applications and GenAI - translating complex business problems into practical architectures that delivery teams can build and scale. This could include architecting an agentic workflow for clinical operations, a conversational analytics product grounded in enterprise data, or an AI-enabled decision platform for commercial teams. You will work directly with clients, define the architecture, test the most important technical decisions yourself and establish the foundations for successful delivery. This is an architecture-first role with meaningful hands-on engineering: you will stay close enough to implementation to prove the architecture works and support it through production delivery, without becoming the primary engineer for every component. You will also help shape the reusable patterns, technical standards and accelerators behind Lynx’s growing AI-native life sciences practice. KEY RESPONSIBILITIES Solution Architecture Own the end-to-end solution architecture for client engagements, including data models, system design, integration patterns and technology choices. Translate business requirements into clear technical designs and implementation paths that delivery teams can build from. Design solutions spanning enterprise data, APIs, applications, cloud platforms and GenAI capabilities. Lead technical discovery with clients: understand requirements, assess existing systems and identify dependencies, constraints and delivery risks. Present architectural options and trade-offs clearly to technical teams, business stakeholders and senior leaders. Make pragmatic decisions across build speed, cost, scalability, security and maintainability. Review key implementation decisions and remain

Help shape the technology that enables a global organisation to do its best work. As Senior Manager, Platform Engineering, you’ll lead the team responsible for Diligent’s Atlassian and Microsoft platforms while setting the architectural direction for the wider internal IT estate. You’ll combine people leadership, enterprise platform strategy and hands-on technical judgement to create secure, reliable and scalable experiences for employees worldwide. From modernising service management and automating joiner, mover and leaver processes to enabling AI safely through Microsoft Copilot and Atlassian Rovo, your work will reduce friction, strengthen governance and deliver measurable business impact. Working across IT, Security, HR, Finance, Legal, Compliance and business teams, you’ll turn complex requirements into well-governed platforms that are easy to use, resilient and ready for the future. Here’s a breakdown of what you’ll do (not all of it, just the important stuff) Lead, coach and grow a global team of platform engineers and systems administrators, building a high-performing and inclusive culture. Own the strategy, architecture, governance and roadmap for Atlassian Cloud, including Jira, Jira Service Management, Confluence, Atlassian Guard and Rovo. Set the direction for Diligent’s Microsoft 365 E5 estate, including Teams, SharePoint, Exchange Online, Intune, Defender, Purview, Power Platform and Copilot. Design scalable integration and automation patterns across identity, HRIS, ITSM and business systems using APIs, event-driven automation, Okta Workflows, Power Platform and scripting. Partner with IT Support to improve self-service, automate repetitive work and reduce ticket volume, escalation effort and time to resolution. Establish strong standards for security, access governance, AI adoption, reliability, compliance and business continuity across the internal technology estate. These are the essentials you’ll need to get an interview Significant experience in i

Today, organizations struggle to ensure their most important digital experiences are working as intended because observability data is scattered across products and siloed in logical layers of their technical stack. We're building the system that fixes this: Journey Monitoring, a single centralized hub that brings together Real User Monitoring (RUM), Synthetics, and Product Analytics to bridge the gap between system health and user success. You'd be building a product that establishes a new functional observability layer, enabling teams to auto-discover journeys, track conversions and uptime side-by-side, and trace root causes across their full stack without cross-team handoffs. What you'll do: Drive the product vision and roadmap spanning the Journey Monitoring hub, including the journey map, details reports, automatically inferred journeys, and cross-product data federation. Own the end-to-end product lifecycle from discovery to launch, working with a cross-functional team of engineers, designers, and other PMs across the Digital Experience Monitoring (DEM) products. Deeply understand the needs of distinct key personas: SREs and engineers (who monitor uptime and troubleshoot technical performance), product managers (who track conversion and investigate behavioral drop-offs), and business leaders (who care about outcomes and revenue impact). Design the functional observability layer that makes end-to-end flow monitoring intuitive — including the auto-discovery of user journeys from real traffic, Experience Level Objectives (XLOs), and seamless Bits AI integrations for automated root-cause investigations. Define how behavioral data and technical data come together to automatically surface whether a drop in conversion is caused by a technical failure (like a breached SLO) or a behavioral friction point. Engage directly with early customers and internal dogfooding users to iterate on usability, refine the journey map, and optimize the cross-sell and up-sell paths for

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! The Sales Ops Specialist role is a strategic leadership role focused on optimizing sales operations, enabling revenue growth, and ensuring alignment between sales execution and company objectives. This exciting career opportunity offers a blend of operational oversight, strategic planning, and cross-functional collaboration. Key Responsibilities Sales Strategy & Execution: Partner with the VP of Sales, Americas to define and implement sales strategies, forecasts, and performance metrics. Operational Excellence: Streamline sales processes, including pipeline management, CRM optimization, and sales enablement tools. Cross-Functional Coordination: Work closely with the ecosystem - inside sales, solution architecture, marketing, product, and customer success teams to ensure cohesive go-to-market execution. Performance Analytics: Monitor sales KPIs, conduct data-driven insights, and recommend adjustments to improve conversion rates and revenue attainment. Team Leadership: Contribute to sales operations, business development, and support functions, fostering a high-performance culture. Stakeholder Management: Serve as a liaison be

Today, everyone from PMs to Sales to SREs uses AI to query their business data - but every answer is a one-off with no governance, no consistency, and no visibility for data teams. We're building the system that fixes this: a context layer that learns from existing data tools driving high quality and consistent answers, an AI-powered query experience, full governance for data teams, and rich analysis surfaces to present and share the results. You'd be building a zero to one product of what we believe will become a major new product line for Datadog. At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What you'll do Drive the product vision and roadmap spanning the Data agent experience, the semantic/context layer, governance console, chat experience and analysis surfaces (dashboards, notebooks, sheets) Own the end-to-end product lifecycle from discovery to launch, working with a cross-functional team of engineers, designers and other PMs Deeply understand the needs of two key personas: data teams (who govern and curate) and data consumers (PMs, engineers, SREs, executives who ask questions) Design the context and governance layer that makes AI-powered analytics trustworthy - including auto-generation from existing BI tools, eval frameworks, confidence scoring, and self-improvement loops Define how observability data and business data come together to serve unique use cases Engage directly with early customers and internal dogfooding users to iterate on accuracy, usability, and trust Independently research the competitive landscape across legacy BI vendors, warehouse-native analytics, AI-first startups, and AI labs Work on the product pricing Work with GTM teams to define positioning, packaging, and the path to displacing entrenched tools Who you are 5+ years of experience

You will lead a small, hands-on engineering team building the secure, scalable Core Analytics Data Access Platform that accelerates Datadog’s Applied AI and analytics capabilities. The team owns the Data Access Platform — a unified interface that lets AI and analytics teams discover and self-serve production-ready datasets while abstracting underlying systems and embedding required legal and compliance guardrails. In this role you’ll own technical direction, contribute to design and code, and partner closely with Applied AI, Product Analytics, and internal platform teams to provide reliable datasets and APIs for model training and analysis. This role balances day-to-day engineering leadership with long-term platform planning. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Lead a Hands-On Engineering Team: Manage, mentor, and grow a small team of 2–4 data engineers (mix of senior and junior) across Paris and NYC, fostering technical excellence and career development. Own Technical Direction and Delivery: Define architecture, engineering priorities, and the team roadmap for the Data Access Platform, driving implementation of scalable, secure data pipelines and platform services. Contribute to Design and Code: Spend substantial time coding, reviewing, and shipping critical platform components to ensure performance, reliability, and operational excellence. Partner with Internal Stakeholders: Work closely with Applied AI, Internal Product Analytics, product managers, and platform teams to define data contracts, APIs, SLAs, observability, and curated analytical datasets. Ensure Data Security, Governance, and Reliability: Implement access controls, lineage, monitoring, and compliance guardrails to support safe model training and repeatable analytics workflows.

CLEAR is building THE secure identity company of the future. Our mission is to make experiences safer and easier—physically and digitally. With more than 43 million Members and a growing network of partners across the world, CLEAR's secure identity platform is transforming the way people live, work, and travel. Whether it’s at the airport, stadium, or throughout your everyday life, CLEAR unlocks the magic of frictionless experiences. Today, CLEAR is well-known as a leader in digital and biometric identification, reducing friction for our members wherever an ID check is needed. We’re looking for a Senior Software Engineer to establish our Observability framework and foundations. You will join us to accelerate building and scaling our innovative systems that support our growing identity platform. You will drive on Observability best practices to find and fix gaps in our observability and our overall systems. You will also lead practices such as load testing, capacity planning, game days, chaos testing, and incident post-mortems. What You Will Do: Embed within the Engineering pillar to deeply understand the product and implement observability across all key flows Facilitate and build load testing cases, ensuring we understand the limits and scaling factors of our services and systems Contribute to observability and support the design of new services and systems, ensuring highly reliable and scalable concepts are implemented Build and lead practices such as game days, chaos engineering, and failure analysis Build long-term capacity plans, with an eye toward reliability and cost-efficiency Who You Are: 6+ experience writing production-grade software in a modern language, such as Java and Python. Strong knowledge of distributed systems concepts (think CAP theorem), microservices architecture, and distributed tracing . Experience with modern observability systems such as Datadog. Experience with performance debugging tools and patterns. You should be able to read a f

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Role Overview: As a Senior Research Engineer in our Safety team, you will play a key role in helping develop safer, more secure, and more reliable models. Your primary focus will be on building tools to enable easy data synthesis, analysis, and management, for complex combinations of real and synthetic data that is used in both model training and evaluation. You will own the cohesive vision of these tooling repositories. You will work closely with a team of research scientists and engineers to create tooling that enables tighter experimentation cycles, better data coverage of the real world, and more scientific rigour. You will have a lot of autonomy and need to be opinionated about what areas of the codebase need elegance and standards, and where that would be overengineering. You will be given high level experimental problems that need to be solved with efficient pipelines, and design and implement the solutions. Your data analysis will collaboratively feed into modelling decisions and experimentation. This role combines expertise in software engineering, statistics, and data science. If any of these topics sound interesting t

Here at Datadog, we think about offensive security a little bit differently. We embrace automation and AI to run adversary simulations continuously across a massive cloud-native environment, and we expect our offensive engineers to build the tooling that makes that possible. We're looking for a Senior Security Engineer who can execute sophisticated red team operations, write the code that scales them, and take an AI-first approach to offensive security engineering. At Datadog, we place value in our office culture - the relationships and collaboration it builds, and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You'll Do: Plan and execute red team engagements end-to-end, simulating real-world threat actors across cloud infrastructure (AWS, GCP), Kubernetes, CI/CD pipelines, and corporate environments Build and maintain custom offensive tooling, automation frameworks, and engagement infrastructure, treating offensive operations as a software engineering problem Develop custom payloads and evasion capabilities tailored to Datadog's environment and modern defensive controls (EDR, SIEM, network monitoring) Improve the efficiency of offensive operations through thoughtful use of automation and AI, accelerating reconnaissance, vulnerability analysis, and reporting workflows Partner with the Detection & Response team on purple team exercises to validate detection logic, improve alert fidelity, and influence threat models Translate offensive findings into concrete improvements by working directly with defensive security and engineering teams to close gaps Who You Are: You have 5+ years of hands-on experience in offensive security (red teaming, penetration testing, or adversary simulation) with a track record of operating against mature, well-defended environments You write production-quality code (Python, Go, or similar), can build your own tools, and automate your w

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We embed deeply with users to solve high-leverage problems. We move quickly from prototype to deployment and surface patterns that shape the platform. We operate at the intersection of customer delivery and core development. We work closely with Product, Research, and Go-To-Market (GTM). About the role We are hiring a Forward Deployed Engineer (FDE) to build and deploy AI systems for legal work. You will embed deeply with customers—often working closely with senior legal practitioners—to identify the right first use case, rapidly prototype a solution, and prove measurable value. Early engagements may focus on creating a “hero” workflow that shows how OpenAI’s models can support legal analysis, drafting, research, or real-time work with complex case records. You will own the technical work from discovery and proof of concept through production adoption, while translating customer workflows and constraints into clear product feedback. As the motion matures, you will turn successful deployments into repeatable patterns that can scale across larger accounts and the broader legal market. This role is based in San Francisco or New York City. We use a hybrid work model of three days in the office per week and offer relocation assistance. Travel up to 50% may be required. In this role, you will Embed with law firms and legal teams to understand their workflows, identify high-value opportunities, and select the right initial use cases to prove value. Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks t