Model Designer in Pune

Artefact is a new generation of data service providers specialising in data consulting and data-driven digital marketing. It is dedicated to transforming data into business impact across the entire value chain of organisations. We are proud to say we’re enjoying skyrocketing growth. The backbone of our consulting missions, today our Data consulting team has more than 400 consultants covering all Artefact's offers (and more): data marketing, data governance, strategy consulting, product owner… What you will be doing? As a Data Engineer, your role involves crafting and maintaining robust data pipelines, utilising Python and SQL, to ensure efficient extraction, transformation, and loading (ETL) of data. Your responsibilities will include: Data Pipeline Development: Building and optimising data pipelines to facilitate seamless data flow across systems and platforms. Database Management: Managing databases, ensuring their integrity, and implementing data storage and retrieval solutions. Cloud Services Integration: Leveraging cloud services such as MS Azure, GCP, and AWS to architect and deploy scalable data solutions. Machine Learning Integration: Collaborating with teams to integrate machine learning models into data pipelines for enhanced data processing. Utilising Spark & Kafka: Implementing and working with Spark and Kafka for real-time data processing and analytics. What we are looking for? Proficiency in Python, SQL, and database management. Experience with Data Pipelines ETL, Cloud Services ( MS Azure, GCP preferred) , ML Modeling, Spark & Kafka. Proven problem-solving skills and a solution-oriented mindset. Excellent communication skills to collaborate effectively within teams and with stakeholders. Strong business acumen with an interest in business-facing roles. Adaptability and a start-up mentality to thrive in a dynamic environment. Candidates with similar skill sets and experiences have excelled in technology firms or consultancy firms. Successful ca

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,400 firms in nearly 60 countries use Addepar to manage and advise on nearly $9 trillion in assets. Its open platform integrates with nearly 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, London, Edinburgh, Pune, Dubai, Geneva, Singapore and São Paulo. The Role Addepar has just launched an Alternatives Product offering that gives Addepar clients the option to have their Private Funds data extracted, processed, validated, and ingested directly from Private Fund documents for a more automated end-to-end solution for handling Alternatives on the platform. This white-glove solution combines proprietary machine learning technology that automatically extracts data from Private Funds documents and human-in-loop review to validate any documents that fail to pass confidence and data quality checks. As a Senior Lead of the Alternatives Data Operations, you will lead the operations function that is responsible for the human-in-loop review of Private Funds documents, ensuring clients' Alternatives data is processed, validated, and available in Addepar in a timely manner. You will manage a team of Alternatives Data Ops analysts who review Private Fund statements, modify data that has been incorrectly extracted by our machine learning models, and reprocess data within SLAs. In this role, you'll own the operational strategy, team performance, and continuous improvement of the Alternatives Data Ops function—a critical component of Addepar's Alternatives offering success. Your responsibilities will include b

Who We Are Addepar is a global data and AI platform empowering investment professionals to turn complex financial information into actionable intelligence. Addepar unifies portfolio, market and client data in a total portfolio view and delivers AI-powered insights within investment and client workflows. More than 1,400 firms in nearly 60 countries use Addepar to manage and advise on nearly $9 trillion in assets. Its open platform integrates with nearly 650 software, data and consulting partners to power end-to-end investment operations across firms of all sizes and complexity. Addepar supports clients worldwide with offices in New York City, Salt Lake City, London, Edinburgh, Pune, Dubai, Geneva, Singapore and São Paulo. The Role Addepar has just launched an Alternatives Product offering that gives Addepar clients the option to have their Private Funds data extracted, processed, validated, and ingested directly from Private Fund documents for a more automated end-to-end solution for handling Alternatives on the platform. This white-glove solution combines proprietary machine learning technology that automatically extracts data from Private Funds documents and human-in-loop review to validate any documents that fail to pass confidence and data quality checks. As part of the broader Addepar Data organization, the Alternatives Data Ops team is responsible for the human-in-loop review of Private Funds documents, ensuring clients' Alternatives data is processed, validated, and available in Addepar in a timely manner. This role will include managing a team and reviewing Private Fund statements, modifying data that has been incorrectly extracted by our machine learning models, and reprocessing the data within SLAs. The Alternatives Data Ops team plays a critical role in the success of Addepar's Alternatives offering and requires daily communications with the Alternatives Product Team, Machine Learning Operations, clients, data providers (GPs and Fund Admins), and add

Overview: We are looking for a Senior Data Engineer with deep expertise in Lakehouse architecture, real-time data streaming, cloud data infrastructure, and microservices development on Azure Kubernetes Service (AKS). You will play a central role in designing and delivering next-generation data pipelines, BI solutions, AI/ML platforms, streaming APIs, and scalable microservices that power Guidepoint's research and analytics products. This is a high-impact, hands-on engineering role. You will work closely with data architects, data scientists, analysts, frontend engineers, QA, and DevOps teams to translate complex business requirements into scalable, reliable, and observable data systems. This is a Hybrid role from our Pune office. What You'll Do: Data Engineering & Lakehouse Design, build, and maintain ETL pipelines, data ingestion workflows, and table schemas on Azure Databricks to support BI, analytics, and AI/ML use cases Architect and optimize the Lakehouse using Delta Lake on Databricks, ensuring reliability, performance, and cost efficiency Build and support data pipelines from business applications such as Salesforce, NetSuite, and other enterprise systems Develop and maintain Knowledge Graph models, entity relationship structures, and NLP-based insight pipelines Maintain data governance, data privacy standards, and compliance best practices throughout the data lifecycle Perform root cause analysis on data and processes to identify opportunities for improvement Collaborate with data architects, scientists, and business consumers to populate and optimize the data warehouse for reporting and analytics Microservices & AKS Development Develop and support scalable web APIs and microservices using Python and Azure Platform Services Build new applications, services, and platforms; optimize existing solutions and refactor legacy components using modern, scalable architec

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. Senior Data Engineer At Snowflake, we are building the future of the data-driven enterprise. We are looking for a Senior Data Engineer who brings deep technical craft, strong ownership instincts, and the ability to operate across the full data lifecycle — from raw ingestion to production-ready data products. This is not a role for someone who executes tickets. You will design and build the data infrastructure that powers internal decision-making and external product capabilities, working at the intersection of data engineering, platform thinking, and stakeholder alignment. You will own complex technical decisions, set the bar for data quality and governance, and contribute to a data platform that scales with the business. The person we are looking for combines engineering rigour with pragmatic judgement — someone who can solve for today while building for the future, and who raises the standard of the teams they work within. AS A SENIOR DATA ENGINEER AT SNOWFLAKE, YOU WILL: Design, build, and launch production-ready data models and pipelines that scale effectively across the enterprise data lifecycle — from ingestion through transformation, modelling, and consumption Own complex system design decisions end-to-end, evaluating tradeoffs and documenting architectural choices c

NVIDIA pioneers computer graphics, gaming, AI, and accelerated computing. We are looking for a Technical Platform Operations Lead to join our team and play an important role in scaling Sales AI applications and platforms. This position offers the opportunity to shape how these solutions operate after launch and help ensure they remain reliable, secure, well governed, widely adopted, and continuously improved. You will collaborate with Sales, Product, Engineering, Data, Security, and IT teams to strengthen platform health, improve the user experience, and increase business impact. What you’ll be doing: Lead end-to-end post-launch operations for Sales AI applications, including availability, performance, support readiness, releases, upgrades, and lifecycle planning. Develop effective processes for incident response, problem management, changes, and issue resolution. Coordinate timely recovery and lasting improvements. Analyze service-level indicators and objectives, adoption metrics, dashboards, alerts, and user feedback to identify risks, performance degradation, and usage gaps. Collaborate with partner teams to translate operational signals and user needs into prioritized improvements and roadmap inputs. Improve adoption and business value through usage analytics, enablement, feedback loops, and user experience enhancements. Establish governance practices for security, access controls, compliance, documentation, and platform support. Develop automation, observability, and self-service capabilities that simplify operations and reduce repetitive work and recurring incidents. Prepare new AI capabilities and releases for production with runbooks, monitoring, rollback plans, support models, and partner enablement. What we need to see: 8+ years of experience in technical operations, pl

NVIDIA pioneers computer graphics, gaming, AI, and accelerated computing. We are looking for a Senior Solution Architect with full-stack software engineering experience to join our team and play an important role in developing Sales AI applications. This position offers the opportunity to design, build, and evolve solutions that bring generative AI and intelligent workflows into everyday sales experiences. You will work across the application stack and collaborate with Product, AI and machine learning, Data, Security, Solution Architecture, and Engineering teams to deliver secure, reliable, and scalable solutions used globally. What you’ll be doing: Collaborate with application teams to design, develop, and maintain scalable full-stack solutions for enterprise sales workflows. Guide technical solutions across front-end, back-end, APIs, data services, integrations, and cloud infrastructure. Translate product requirements and business needs into secure, maintainable solutions and intuitive user experiences. Integrate generative AI models, AI services, APIs, retrieval systems, and agentic workflows into production applications. Design application architectures that support performance, availability, observability, security, scalability, and long-term maintainability. Lead technical design discussions, compare implementation approaches, make informed architecture decisions, and evaluate emerging technologies. Improve engineering practices for testing, code quality, continuous integration and delivery, monitoring, documentation, and production readiness. Investigate complex issues and develop solutions that improve reliability and user experience. Mentor engineers, share technical knowledge, and contribute to engineering standards and collaborative team practices. What we need to see: <