Data Engineer

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

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

Key Responsibilities Enterprise Data Strategy & Client Engagement: Develop and maintain a comprehensive data architecture strategy that aligns with organizational and client business objectives. Serve as a key technical advisor for clients, translating business requirements into innovative data solutions. Build and maintain strong client relationships by providing expert guidance and managing expectations throughout project lifecycles. Data Modeling, Design & Engineering: Design and optimize both logical and physical data models to support enterprise-wide systems. Architect data warehousing solutions, overseeing the integration of data from multiple sources to enable robust business intelligence and analytics. Directly develop, test, and implement ETL processes and data pipelines, ensuring data quality, consistency, and performance. Technology Evaluation & Implementation: Evaluate emerging data technologies and tools to determine their fit within the existing architecture and potential for future scalability. Oversee the integration of new technologies into the enterprise data architecture, balancing innovation with risk management. Team Leadership & Hands-On Management: Lead cross-functional teams, providing mentorship and technical guidance to junior data engineers and architects. Maintain a hands-on approach by actively participating in coding, design sessions, and troubleshooting complex data issues. Ensure project milestones are met through effective resource management and team coordination. Performance, Security & Best Practices: Optimize data storage, retrieval, and processing performance across various systems. Collaborate with security teams to enforce data governance, compliance, and privacy standards. Establish and promote best practices in data management, data engineering, and architecture design. Documentation & Reporting: Develop and maintain comprehensive documentation covering data architecture designs, data flows, integrati

We are expanding our agentic AI capability and are looking for an AI Engineer to join the team. You will work alongside senior engineers to build and maintain AI systems — contributing to agentic pipelines, retrieval infrastructure, and the integrations that tie these systems together. This is a hands-on implementation role with real ownership of components. You will grow your skills in a fast-moving AI practice, working on production systems that directly affect client outcomes. What This Involves: Build and maintain agentic pipelines and workflows under the guidance of senior engineers: tool use, orchestration, and multi-step reasoning. Implement and tune RAG pipelines — including embedding, chunking strategies, vector retrieval, and retrieval evaluation. Contribute to memory and context layer components: integrating vector databases, supporting knowledge graph pipelines, and helping maintain state management across agentic systems. Write clean, well-tested Python code and participate in code reviews. Debug and improve existing AI systems based on evaluation results and production feedback. Collaborate with data engineers and domain experts to integrate AI components with upstream data sources and downstream applications. Document implementations clearly and contribute to shared internal tooling. Requirements: 2–4 years of software or ML engineering experience, with at least 1 year working with LLMs or AI systems in a professional setting. Working knowledge of LLM APIs (OpenAI, Anthropic, or similar) and at least one agentic or RAG framework (LangChain, LlamaIndex, or equivalent). Solid Python skills and comfort with software engineering basics: version control, testing, REST APIs. Familiarity with vector databases or embedding-based search. Curiosity about agentic AI — you follow developments in the space and are eager to apply new techniques. Excellent communication and collaboration skills — comfortable working across cross-functional and client-facing te

Our Purpose Mastercard powers economies and empowers people in 200&#43; countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Manager, Software Engineering Overview We are seeking a hands-on Manager, Software Engineering to lead the development of scalable data platforms, backend systems, and data pipelines supporting Mastercard's Portfolio Intelligence products. This role will initially focus on leading a team of Data Engineering contractors while providing strong technical leadership across architecture, delivery, and engineering excellence. The ideal candidate is a recent practitioner who has built and operated modern data platforms and backend services, can confidently review architecture proposals and code, and leverages AI-powered engineering tools to improve productivity, quality, and delivery speed. As the team evolves, this leader will play a key role in building and developing a high-performing organization of full-time engineers. What You'll Do Technical Leadership Provide technical leadership for backend services, data pipelines, and platform capabilities that support analytics, reporting, and AI-driven products. Review architecture and design documents to ensure solutions are scalable, maintainable, secure, and aligned with long-term platform strategy. Conduct and oversee code reviews, promoting engineering best practices, reliability, security, and operational excellence. <br