Analytical Engineer Salary India Jobs

About the Team The Spark Platform team owns and operates DoorDash's Apache Spark ecosystem — the execution runtime, remote shuffle service, cluster scheduler, and reliability tooling that powers the company's data, analytics, and ML workloads. We run Spark across the company at significant scale and continue to expand the workloads, capabilities, and consumer base we serve. Orchestrating and operating thousands of Spark cluster deployments is a complex distributed system problem which the team invests heavily in runtime optimization, systems architecture, multi-tenant scheduling, and end-user tooling. About the Role As a Software Engineer on Spark Platform, you will execute across the surfaces of our in-house Spark deployment that serves the entire company. The work spans Spark runtime upgrades and performance, multi-tenant scheduling and executor bin-packing on Kubernetes, cluster lifecycle automation, and the observability and incident automation that keep the platform sustainable. You will move between layers as the work demands — picking up the next high-leverage problem regardless of where it sits — and partner closely with the rest of the team and with platform consumers across the company. You must be located in San Francisco, Sunnyvale, Seattle, or New York City for this hybrid position. You will report into the Engineering Manager on our Spark Platform team. You're excited about this opportunity because you will… Build and operate an in-house Spark platform that runs at company-wide scale, spanning runtime, scheduler, reliability, and user-facing tooling. Drive multi-tenant scheduling, executor bin-packing, and cost-aware placement that let a small team serve dozens of consumer teams. Own pieces of cluster lifecycle automation — provisioning, upgrades, capacity changes, and node-failure handling — at a scale where these stop being manual events. Build the observability and incident automation that make the platform debuggable end-to-end and keep on-call sus

Staff Software Engineer - UI Foundation at Amplitude (View all jobs) San Francisco Bay Area Hybrid Amplitude is the leading AI-first digital analytics platform, helping over 4,300 customers—including Atlassian, Burger King, NBCUniversal, Square, and Under Armour—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Fall 2025 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. The UI Foundation team owns the frontend infrastructure that every product engineer at Amplitude builds on — architecture, performance, developer experience, tooling, and build systems. We're the team that makes shipping fast, reliable frontend code possible at scale, and we're increasingly focused on how AI agents can autonomously handle engineering workflows that used to require constant human intervention. The Role We're looking for a Staff Software Engineer who thinks like an infrastructure engineer but has deep fluency in frontend systems. You'll drive architectural decisions for our frontend platform, push performance and DevX forward, and lead the build-out of our "software factory" — a set of autonomous, AI-agent-driven engine

Staff Software Engineer - UI Foundation at Amplitude (View all jobs) San Francisco Bay Area Hybrid Amplitude is the leading AI-first digital analytics platform, helping over 4,300 customers—including Atlassian, Burger King, NBCUniversal, Square, and Under Armour—build better products and digital experiences. With powerful AI Agents embedded across our platform, teams can analyze, test, and optimize user experiences faster than ever. Ranked #1 across multiple categories in G2’s Fall 2025 Report, Amplitude is the best-in-class solution for product, data, and marketing teams. Learn more at amplitude.com . As an organization, we deliver for our customers by living our values. We operate from a place of humility, take ownership of problems and successes, approach challenges with a growth mindset, and put our customers at the center of everything we do. Amplitude’s Commitment to Diversity Equity & Inclusion (DEI): Amplitude believes that diversity enables the creation of better products, improves the ability to solve complex problems, and drives more powerful solutions. We strive to create an environment of inclusion—one focused on psychological safety, empathy, and human connection—that will allow employees of all backgrounds to thrive. The UI Foundation team owns the frontend infrastructure that every product engineer at Amplitude builds on — architecture, performance, developer experience, tooling, and build systems. We're the team that makes shipping fast, reliable frontend code possible at scale, and we're increasingly focused on how AI agents can autonomously handle engineering workflows that used to require constant human intervention. The Role We're looking for a Staff Software Engineer who thinks like an infrastructure engineer but has deep fluency in frontend systems. You'll drive architectural decisions for our frontend platform, push performance and DevX forward, and lead the build-out of our "software factory" — a set of autonomous, AI-agent-driven engine

About the Team Data Platform at OpenAI owns the foundational data stack powering critical product, research, and analytics workflows. We operate some of the largest Spark compute fleets in production; design, and build data lakes and metadata systems on Iceberg and Delta with a vision toward exabyte-scale architecture; run high throughput streaming platforms on Kafka and Flink; provide orchestration with Airflow; and support ML feature engineering tooling such as Chronon. Our mission is to deliver reliable, secure, and efficient data access at scale and accelerate intelligent, AI assisted data workflows. Join us to build and operate these core platforms that underpin OpenAI products, research, and analytics. We’re not just scaling infrastructure – we’re redefining how people interact with data. Our vision includes intelligent interfaces and AI-assisted workflows that make working with data faster, more reliable, and more intuitive. About the Role This role focuses on building and operating data infrastructure that supports massive compute fleets and storage systems, designed for high performance and scalability. You’ll help design, build, and operate the next generation of data infrastructure at OpenAI. You will scale and harden big data compute and storage platforms, build and support high-throughput streaming systems, build and operate low latency data ingestions, enable secure and governed data access for ML and analytics, and design for reliability and performance at extreme scale. You will take full lifecycle ownership: architecture, implementation, production operations, and on-call participation. You’ve supported Spark, Kafka, Flink, Airflow, Trino, or Iceberg as platforms. You’re well-versed in infrastructure tooling like Terraform, experienced in debugging large-scale distributed systems, and excited about solving data infrastructure problems in the AI space. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per wee

About the Team: The Database Systems team specializes in high-performance distributed databases. Our team built Rockset, the real-time search, analytics, and vector database that powers all vector search and retrieval augmented generation (RAG) at OpenAI. In addition to retrieval, as an online database, Rockset powers core functionality across all of OpenAI's product lines and many critical internal use cases. About the Role : We are looking for engineers passionate about distributed systems, close-to-the-metal performance optimization (our core engine is written in C++), and building scalable database infrastructure from the ground up. As an engineer on the Database Systems team, you'll contribute to the core database engine, driving improvements across ingestion, query execution, indexing, and storage. You'll partner with teams across OpenAI to unlock new product capabilities and help scale online database reliability and throughput as usage grows by orders of magnitude. In this role you will: Design, build, and operate high-performance distributed systems Identify and resolve performance bottlenecks to scale infrastructure to the next order of magnitude Define long-term technical direction and guide system evolution Collaborate with product, engineering, and research teams to deliver scalable and reliable infrastructure Dig deep into complex production issues across the stack Contribute to incident response, postmortems, and best practices for system reliability You might thrive in this role if you: Have significant experience building, scaling, and optimizing distributed systems at scale Are curious about database internals, storage engines, or low-latency query systems Enjoy debugging challenging performance issues in complex, high-throughput systems Have experience operating production clusters at scale (e.g., Kubernetes or other orchestration systems) Think rigorously about scalability, correctness, and reliability Thrive in fast-paced environments with high

About the Team The Statsig team within OpenAI owns the experimentation, rollout, dynamic configuration, and analytics infrastructure that sits on the launch path for OpenAI products. Our systems help teams ship safely, evaluate product and model changes in production, and make high-confidence decisions from real-world usage. Statsig began as an independent company built around experimentation, feature management, and product analytics at scale. After Statsig joined OpenAI, the team began the next chapter: bringing that platform expertise and infrastructure into OpenAI as the experimentation and rollout foundation for every product we ship. This is infrastructure with a very direct product consequence. Teams working on ChatGPT, Codex, model measurement, consumer experiences including ads, business subscriptions, developer products, and shared platform systems depend on Statsig to evaluate configurations, move traffic safely, ingest experiment data, serve analytics, and roll changes forward or back when production reality demands it. We are at a critical point in the platform journey. Adoption is accelerating quickly across OpenAI, and the systems that were already important are becoming load-bearing for how the company launches. The infrastructure needs to stay fast under sharply increasing evaluation volume, reliable when more services depend on it, observable enough to debug quickly, and efficient enough to support OpenAI-wide scale. Recent SDK and server-side infrastructure work has already produced measurable wins in latency, reliability, memory usage, and compute efficiency across important services. The next phase is to make those gains systematic: a platform that can absorb rapidly growing product velocity while preserving low latency, data quality, operational safety, and developer trust. Based out of OpenAI's Bellevue office, we are a close-knit team that values in-person collaboration, technical depth, operational ownership, and building infrastructure that

About the Team The Statsig team within OpenAI builds the experimentation, feature rollout, dynamic configuration, and analytics systems that help OpenAI ship products with speed, safety, and evidence. Our work sits on the critical path for how product, engineering, research, and go-to-market teams learn from real-world usage and make high-confidence decisions. Statsig began as an independent company focused on helping builders move faster through trustworthy experimentation and feature management. After Statsig joined OpenAI, the team began the next chapter: bringing that deep product expertise, customer intuition, and mature platform infrastructure into OpenAI as the experimentation and rollout platform for every product we ship. Today, we support teams across ChatGPT, Codex, model measurement, consumer experiences including ads, business subscriptions, developer products, and the shared infrastructure that connects them. These teams rely on Statsig to safely introduce new capabilities, compare product and model behavior, measure impact, and roll changes forward or back with confidence. We are at a defining moment in the platform journey. OpenAI has the data, product surface area, and pace of innovation to learn faster than almost any organization in the world, but that potential only becomes real if teams can experiment responsibly, measure clearly, and roll out changes safely. Adoption of the platform is accelerating rapidly across the company, and recent SDK and server-side infrastructure work has already produced measurable wins in latency, reliability, memory usage, and compute efficiency for important services. Based out of OpenAI’s Bellevue office, we are a close-knit team that values in-person collaboration, urgency, craft, and impact. We build for other builders, and the best version of this team is one where every OpenAI product team can move faster because the experimentation and rollout layer is dependable, fast, and easy to use. About the Role We are l

Shape the Future with Dun & Bradstreet At Dun & Bradstreet, we believe data has the power to create a better tomorrow. As a global leader in business decisioning data and analytics, we help companies worldwide grow, manage risk, and innovate. Since 1841, businesses have trusted us to turn uncertainty into opportunity. We’re a diverse, global team that values creativity, collaboration, and bold ideas. Are you ready to make an impact and help shape what’s next? Join us! Explore opportunities at dnb.com/careers. The Software Engineer II is responsible for designing, developing, and delivering scalable data platform solutions that support high-performance data processing and analytics capabilities. This role operates with increased autonomy, contributing to system design, driving delivery of platform capabilities, and ensuring the reliability and scalability of the Dun & Bradstreet data ecosystem. The role plays a key part in modernizing and optimizing data platforms, including identity resolution and Match systems, to meet growing business demands.

The Performance Research Engineer will play a critical role in advancing TaylorMade's leadership in golf equipment performance. This role bridges physical testing, player testing, Tour-level data collection, and advanced analytics to deliver actionable insights that influence product design, product validation, and performance optimization. The ideal candidate is a hands-on engineer with strong mechanical aptitude, advanced data skills, deep golf intuition, and the ability to translate player feedback into clear engineering direction. Essential Functions and Key Responsibilities: Lead the design and execution of advanced performance testing protocols for golf clubs and balls, including lab, player, field, and Tour-based testing environments. Serve as a category-focused Performance Engineering owner for one or more product areas, with potential emphasis across Woods, Irons, Putter/Wedge, or cross-category initiatives. Support PGA/LPGA Tour and elite-athlete testing by collecting clean, repeatable, decision-ready data while operating professionally and respectfully in player-facing environments. Analyze large datasets from lab, player, and field testing to extract insights on ball speed, launch, spin, consistency, delivery, impact location, dispersion, and performance tradeoffs. Translate Tour and player-test observations into clear engineering recommendations, product questions, validation plans, and follow-up experiments. Develop and maintain automated data pipelines, dashboards, and reporting tools for performance tracking, project communication, and cross-functional decision-making. Collaborate with R&D, Product Development, Tour, Fitting, Consumer Insights, and Analytics teams to integrate player feedback and real-world data into product design.

About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog makes products self-driving . It's the only platform that acts like a co-pilot for you (and your AI agents) to do it all – autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Desktop , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change wh

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Driver team is dedicated to fostering a platform of high-quality service by empowering drivers to perform their best. We are looking for a product-minded engineer who wants to build and improve products that sit at the center of the core driver experience. Products you drive will solve pain points that matter most to drivers by streamlining key interactions, reducing friction, and creating systems that feel intuitive, fair, and supportive. As an engineer at Lyft, you'll collaborate with teams like product, data science, analytics, and operations on code that empower us to iterate quickly, while focusing on delighting our passengers and drivers. Responsibilities: Design and implement backend features end-to-end with clear ownership, delivering well-scoped work from technical design through to production with moderate guidance from senior engineers Write clean, reliable, well-tested code that meets team standards and holds up in code review Participate actively in code reviews, giving specific and constructive feedback while continuing to develop your own review instincts Debug and resolve issues across backend services including performance bottlenecks, reliability problems, and data integrity issues Collaborate with product managers, designers, and partner engineering teams to clarify requirements and surface technical constraints early Contribute to technical discussions and help evaluate implementation approaches for new features Write unit and integration tests for your own code and develop familiarity with the team's broader testing and observability practices Address technical debt and make incremental improvements to existing services as part of regular development work Participate in on-call rotations, respond to production incidents, and support teammates in mitigating custome

Here's a summary of the role: You're a hands-on engineer who enjoys solving complex data challenges at scale. You'll join the Data Hub team, building the shared data platform that supports reporting, analytics, AI, and Data Science initiatives across Diligent. Working with Python, SQL, AWS, and cloud-native technologies, you'll help process, organize, and enrich large volumes of data while developing scalable services and modern data solutions. You'll collaborate closely with Product Managers, Engineering Managers, and fellow engineers to deliver high-quality features, improve platform capabilities, and shape the future of our data ecosystem. If you enjoy ownership, solving challenging problems, experimenting with new technologies, and working in a collaborative environment, you'll fit right in. Here's a breakdown of what you'll do (not all of it, just the important stuff): Design, develop, review, and test features and user stories following Agile development practices Contribute to core platform development and integration projects across multiple systems Participate in shaping the future architecture of the product , including designing scalable backend services and prototypes Collaborate with Product Owners and Engineering Managers to analyze, refine, and document technical requirements Build and maintain cloud-native solutions and microservices-based applications Leverage AI-assisted development tools , code assistants, and modern engineering workflows to improve delivery efficiency Support the creation and maintenance of high-quality operational and technical documentation Continuously identify opportunities to improve engineering processes, quality, and team effectiveness These are the essentials you'll need to get an interview: 2+ years of experience in a hands-on software development role within a commercial software environment Strong programming experi

Quality Engineer (Associate or Experienced) Company: The Boeing Company Boeing Defense, Space and Security (BDS) has an exciting opportunity for an Quality Engineer (Associate or Experienced) to join the Quality Fabrication team in Hazelwood, MO! This position supports the production line by leading root cause investigations and corrective actions for nonconformances (NCRs), performing line stock checks and data analytics to identify trends, and presenting to stakeholders. The role works closely with production, quality, supply chain and engineering to ensure timely containment and permanent corrective actions that reduce recurrence and improve process capability. Position Responsibilities: Researches contractual and Boeing Quality Management System requirements for applicability to specific proposals and program processes and documentation. Develops sections of quality metrics, design and production certification plans to ensure compliance with contractual, Company and regulatory requirements. Analyzes capability assessments to support supplier selection activities. Participates in various reviews to ensure quality attributes are incorporated into product designs. Performs data analysis to ensure manufacturing and test readiness. Provides material review dispositions for non-conformances. Analyzes non-conformance trends to evaluate effectiveness of corrective actions. Compiles performance reports and other statistical data to ensure specified processes capability levels are achieved. Works under general supervision. Basic Qualifications (Required Skills/Experience): Bachelor of Science from an accredited course of study

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The Data Product Experiences (DPE) team is dedicated to making Stripe's merchant-facing data products intuitive, delightful, and actionable. We build client-side rendering engines, high-performance charting libraries, and interactive visualization interfaces that handle high-throughput streaming telemetry and real-time merchant analytics. What you’ll do In this role, you will architect and build high-performance client-side data rendering engines from scratch to visualize tens of thousands of data points smoothly. You will collaborate closely with Designers, Product Managers, and Front-End Systems Engineers to define cutting-edge data visualization paradigms that reduce cognitive load and prevent visual fatigue for Stripe's users. Responsibilities Partner with designers and product managers to prototype, build, and ship interactive analytics dashboards and data visualization tools across the Stripe Dashboard. Contribute to Stripe’s core design system by developing scalable, reusable visualization components and charting standards for engineering teams. Design frontend integration strategies and robust API contracts to enable seamless adoption of analytics components by partner teams. Provide technical leadership and mentorship through code reviews, pairing, and fostering frontend engineering best practices. Collaborate across Product, Design, Data Infrastructure, and Analytics teams to deliver high-quality, data-driven user experiences. Opti

Who we are About Stripe Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career. About the team The Data Product Experiences (DPE) team is dedicated to making Stripe's merchant-facing data products intuitive, delightful, and actionable. We build client-side rendering engines, high-performance charting libraries, and interactive visualization interfaces that handle high-throughput streaming telemetry and real-time merchant analytics. What you’ll do In this role, you will architect and build high-performance client-side data rendering engines from scratch to visualize tens of thousands of data points smoothly. You will collaborate closely with Designers, Product Managers, and Front-End Systems Engineers to define cutting-edge data visualization paradigms that reduce cognitive load and prevent visual fatigue for Stripe's users. Responsibilities Partner with designers and product managers to prototype, build, and ship interactive analytics dashboards and data visualization tools across the Stripe Dashboard. Contribute to Stripe’s core design system by developing scalable, reusable visualization components and charting standards for engineering teams. Design frontend integration strategies and robust API contracts to enable seamless adoption of analytics components by partner teams. Provide technical leadership and mentorship through code reviews, pairing, and fostering frontend engineering best practices. Collaborate across Product, Design, Data Infrastructure, and Analytics teams to deliver high-quality, data-driven user experiences. Opti