Data Engineer in India

Test Engineering Data Technician (EDT) — Sanand - 303A - AT/SSD/MOD, India. Apply via Workday.

Staff Data Science Engineer, SMAI — Hyderabad - Phoenix Aquila, India. Apply via Workday.

To lead the enterprise data architecture and data platform engineering initiatives for Adani Airport Holdings Limited, driving the digital transformation of airport operations. This role focuses on designing highly available, secure, and scalable data analytics platforms leveraging Databricks on Microsoft Azure cloud to enable real-time situation awareness, data-driven decision-making, optimize passenger flow, and support the strategic growth of AAHL’s aviation ecosystem. Source: Adani Group | Job ID: 53636

Job Details: Job Description: Intel's Design Quality and Reliability organization is seeking an AI Platform Engineer to architect and build an enterprise-grade AI platform for mission-critical engineering work. This platform will enable Intel engineers to analyze complex design, qualification, and reliability data; automate engineering workflows; access organizational knowledge; and make faster, evidence-based decisions throughout the product lifecycle. The successful candidate will combine strong software engineering fundamentals with expertise in AI-native and agentic development. They will be highly proficient with Agentic AI coding assistants and able to use these tools responsibly to accelerate architecture, implementation, testing, debugging, and documentation. This role requires close collaboration with Design, Quality and Reliability, Product Engineering, Manufacturing, IT, Information Security, and other Intel stakeholders. Responsibilities 1. Architect and develop Intel's reusable AI platform for Design Quality and Reliability. 2. Build AI agents and workflows for engineering data analysis, qualification planning, risk assessment, knowledge retrieval, reporting, and process automation. 3. Apply Agentic AI coding assistants to accelerate software development while maintaining rigorous engineering review and validation. 4. Integrate AI capabilities with Intel engineering databases, quality-management systems, internal APIs, spreadsheets, documentation repositories, and workflow tools. 5. Develop production-grade backend services, APIs, data pipelines, model gateways, and agent-orchestration components. 6. Establish shared platform capabilities for identity, access control, tool authorization, memory, observability, evaluation, and auditability. 7. Implement human approval, deterministic validation, and rollback controls for consequential engineering actions. 8.

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. Senior Data Analyst - Field Analytics As part of Okta’s Go-To-Market Strategy & Operations group, the Field Analytics team drives insight and scale within the global field organization. We serve as the core engine for the analytics and strategic analysis that enable our leaders to make data-driven decisions that determine the trajectory of Okta’s growth. You will be responsible for building high-impact technical assets, ranging from executive Tableau dashboards to standardized Snowflake datasets, while staying at the forefront of AI-driven analytics workflows. You will partner with US-based leadership and local team members to ensure our reporting framework is scalable, accurate, and deeply aligned with Okta’s global GTM strategy. Job Duties & Responsibilities: Analytics Delivery: Design, build, and maintain high-visibility Tableau dashboards and reporting assets that provide actionable insights to business partners across the global organization Data Set Engineering: Build and optimize production-grade data sets in Snowflake, ensuring that all field data (Pipeline, Bookings, Productivity) is clean, structured, and easily accessible for self-service analysis. Documentation & Governance: Take ownership of the technical documentation for all GTM reporting assets, ensuring data lineage, metric definitions, and logic are clearly defined and accessible. AI Implementation: Champion the use of Generative AI tools to accelerate the analytics lifec

We’re looking for a technical force multiplier to work directly with the founders at Bolna.ai . This is not a traditional Chief of Staff, PM, or engineering role. It sits at the intersection of strategy + product + engineering. Your job is simple: take messy, important problems, figure out what matters, and make things happen. What you’ll do Find and build ways to leverage AI internally to dramatically improve engineering velocity and company operations. Dive into product, business, growth, and engineering data to uncover insights and turn them into clear, actionable recommendations. Work across Engineering, Product, and Growth to supercharge teams, remove bottlenecks, and unlock leverage through technology. Pick up ambiguous, high-leverage problems and drive them end-to-end. One day could mean discovering and iterating on a new tool in the morning, building a prototype that afternoon, and shipping it by the end of the day. Who we’re looking for You have high agency and a founder’s mindset . You’re technically strong enough to build prototypes, deeply curious about how things work, and fast at learning unfamiliar domains. You have strong product and business intuition, can reason from messy data, and communicate clearly in writing. You’d rather skip a one-hour meeting to spend that hour chasing a curiosity that could create 10x the impact . You know that disproportionate outcomes often come from asking the question nobody assigned you to ask. You don’t wait for perfectly scoped tasks. Depending on the problem, you’re comfortable researching, coding, analyzing data, talking to customers, testing a product, or coordinating a team. Most importantly, you have good judgment about what is worth pursuing . If you’re an ex-technical founder or founding engineer , this role will likely feel familiar: high ambiguity, high ownership, and a bias toward figuring things out yourself. We operate with a simple belief: AI, when applied skillfully to the right problems, can create di

Instawork is on a mission to create meaningful economic opportunities for skilled hourly professionals in communities around the globe. Our AI-powered labor marketplace helps local businesses scale, and enables global technology companies to push the frontiers of robotics and AI. Backed by world-class investors like Benchmark, Spark Capital, Craft Ventures, Greylock, Y Combinator, and others, we’re looking for exceptional talent to reimagine the way the world works. About IRL (Instawork Robotics Labs) Researchers at UC Berkeley have identified a “100,000-year data gap” - the gulf between what trained AI language models and what physical robots actually have to learn from. Closing that gap is the defining infrastructure challenge of the physical AI era. IRL is Instawork’s answer to it. We deploy skilled workers into real commercial and residential environments - kitchens, warehouses, hotel floors, homes - to capture the high-fidelity task data that the world’s leading Robotics labs use to train their foundation models. Read more here . What you’ll do Lead Workforce & Operations: Drive day-to-day workforce management for Clippers, Graders, Regraders, SMEs, and ICs across shifts/sites, optimizing staffing, capacity planning, and throughput against SLA targets. Implement Quality Systems & Methods: Maintain the QMS and apply structured methods (RCA, CAPA, FMEA, 8D, SPC) to address recurring defects, calibration drift, gold-sample injections, and consensus checks. Own SOPs & Process Standards: Build, version-control, and continuously iterate SOPs for existing and new program launches, ensuring floor adoption and structured QA onboarding/re-calibration paths. Bridge Cross-Functional Teams: Translate engineering data requirements into floor-executable QA criteria, report field issues back with evidence, and represent QA in program launches and crisis calls. Drive Data-Led Quality: Monitor and analyze key QA metrics—defect/reject rates, inter-grader agreement (ka

About the Team Meesho is on a mission to enable 100 million businesses to succeed online. With your help, we can go beyond!We’re making e-commerce accessible for tier-2+ markets who are new to e-commerce and have almost never transacted online before Our Design team is as diverse as our users. Today, the team comprises of 30 Designers – including Interaction and Visual Designers As Product Designer, you’ll be part of a team solving unique problems, one that’s mostly untouched by other e-commerce players. But wait, there’s more! We’re individuals who are obsessed with our users. We empathise. We solve at grassroots levels. We’re breaking all the barriers -- be it language, literacy, culture, or technology💪 But wait, there’s more! We’re individuals who are obsessed with our users. We empathize. We solve at grassroots levels. We’re breaking all the barriers -- be it language, literacy, culture, or technology:muscle: If you’re someone who wants to work at a place that creates massive impact, then join us. About the Role Passionate about Design? Find deep-diving into data exciting? Then you might be our next Product Designer🤩 As a Product Designer, you’ll define user goals, scenarios, benefits, and flows as well as own end-to-end experiences from a design perspective. You’ll work closely with Product, Business, Data and Engineering teams to create delightful and impactful experiences for our users. In this role, you’ll break down complex tasks by understanding customer and business needs and translate them into easy to use, intuitive and delightful designs. Your end goal will be to find ways to improve processes to enhance experiences for customers. You'll be able to quickly communicate your decisions and solutions verbally as well as through sketches, user flows, wireframes, hi-fi mocks and functional prototypes.

Senior /Staff Data & Cloud Platform Engineer — Hyderabad - Phoenix Aquila, India. Apply via Workday.

Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as our next Senior Engineering Manager , Twilio’s Segment team. About the job As a Senior Engineering Manager on the Twilio Segment Data platform/ pipelines team, you’ll build and scale systems that process several hundred thousands of data points per second. You will lead the development of high-scale ingestion and data processing systems You'll guide the team in designing, operating and maintaining complex distributed systems, ensuring reliability, performance, and cost-efficiency while querying petabytes of data for our customer data platform (CDP). Responsibilities In this role, you’ll: Own and deliver robust, high-scale routing experiences for Data platforms & pipelines for Twilio Segment. Champion team growth and success, prioritizing mentorship and individual development. Architect and operate always-available, complex distributed systems in cloud environments. Guide technical decisions, articulating trade-offs between cost, p

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About the Role Adobe is seeking a Machine Learning Engineer to join the Adobe Genuine Engineering team. This group protects Adobe's ecosystem from fraud, abuse, and misuse using intelligent systems worldwide. In this position, you will build and develop machine learning models from scratch, including custom transformer-based frameworks, to identify fraudulent actions, stop account sharing, and protect the experience of hundreds of millions of users. You will manage the entire model lifecycle: raw behavioral data and feature engineering, architecture development, large-scale GPU training, deployment, and monitoring. The team is actively building in-house behavioral foundation models that learn identity-preserving representations from long sequences of user activity. This is a role for an engineer who wants to own deep learning systems end-to-end — not consume pre-built ones. Key Responsibilities Build and train deep learning models from scratch, including custom transformer and attention-based architectures for long behavioral event sequences. Own the full training stack: event tokenization, temporal and positional embeddings, self-supervised pretraining (e.g., masked modeling, contrastive learning), and downstream fine-tuning. Train large models efficiently on GPU infrastructure using mixed-precision training, gradient accumulation/checkpointing, efficient attention, and distributed strategies (DDP, FSDP, or equivalent). Build and optimize feature pipelines on Databricks and Spark, transforming raw behavioral events into high-quality model inputs. Translate prototypes into production ML systems — scalable, reliable, and observable — and drive inference performance through architectural and serving-side optimization. Contribute to MLOps practices: experiment tracking, model versioning, CI/CD, automated retraining, and

About Ema Ema is building the world’s leading Agentic AI platform to transform enterprise productivity. We enable organizations to delegate repetitive tasks to Ema, the Universal AI Employee, delivering 10x gains in workforce efficiency, across functions. Founded by former executives from Google, Coinbase, Flipkart, and Okta, our team includes engineers from premier tech companies and graduates of Stanford, MIT, UC Berkeley, CMU, and IITs. We are backed by industry leading investors including Accel, Naspers/Prosus, Section32, and angels like Sheryl Sandberg and Dustin Moskovitz. Headquartered in Silicon Valley and with offices in London, Bangalore and Vancouver, Ema is at the frontier of what Agentic AI can do in production — we ship real systems that run real business processes at scale. The Role We are looking for an Engineering Leader to manage and scale multiple product lines in the Voice, BPO, and Workforce Management space. This is a high-impact leadership role that sits at the intersection of real-time voice systems, operations research, and data-intensive platform engineering. You will report directly to the Head of Engineering and own the engineering organization that builds the infrastructure powering Ema’s Voice AI Employees, Agent QA, auto-learning pipelines, rich analytics, and workforce optimization capabilities — all operating as scalable, multi-tenant systems deployed across global geographies. You will collaborate with Product, ML/AI, and Go-to-Market teams to translate customer needs into production systems that handle high volumes of voice data, deliver real-time insights, and continuously improve through automated learning loops. As the owner of multiple product lines, you will balance roadmap priorities across Voice, BPO operations, and WFM (work force management) — ensuring each product evolves cohesively while meeting distinct customer needs. What You Will Do Scalable Multi-Tenant Systems Architect and build multi-tenant systems that serve ent

mthree Gradate Recruitment Program: Tech Roles About Us: mthree gives you a foot in the door to your dream career! We’ve helped 4,000 people start careers in technology, banking and business. For graduates and anyone starting their career, you’ll start with 6-12 weeks of training at our Academy. Then you’ll join one of our clients for 12-24 months (we work with investment banks and other big companies in industries from healthcare to aviation to insurance). You’re supported by us throughout, with pay rises every 12 months and an online learning plan to develop your skills. Afterwards, the majority continue their career with the client. At mthree, we believe in fairness from the start. We don’t lock you in with exit fees. You’ll never have to pay a thing. Join mthree to unlock your potential and go further than you thought possible. What you’ll do: If successful, you’ll work with one of our clients as an mthree Alumni designing, building, testing, and maintaining scalable and stable off-the-shelf applications or custom-built technology solutions. Also, working with a global team, you’ll help support systems including algorithmic trading engines and regulatory reporting. What you need: Degree in Computer Science, Technology, or related STEM subjects Academic aggregate of 60% or higher with no standing arrear Strong programming skills: Java/ Python/ C/ C++/ Others Competitive coding experience will be an added advantage Good troubleshooting and debugging skills Solid software engineering principles (data structures, OOPs, design patterns, multithreading) Understanding of the formal software development lifecycle (SDLC) Understanding of test-driven development How it works: Stage 1: Apply for the position Stage 2: Clear the first round of Aptitude & Coding assessment Stage 3: Clear communication Screening Stage 4: Clear Technical interview Stage 5: Clear Final interview Stage 6: Get selected to join the train