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Experienced Solutions & Data Architect with a demonstrated history of working in the…
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Satyen Mehta liked thisSatyen Mehta liked thisData engineering has levels. You do not become advanced by collecting tools. You become advanced by building the right foundations first. At the basic level, the focus is simple: → Git and version control → ETL / ELT fundamentals → Data modeling → Databases and warehouses → Python → SQL These skills teach you how data is structured, moved, transformed, queried, and maintained. Then comes the intermediate layer. This is where you start working with production-grade systems: → Docker for portable environments → dbt for modular SQL transformations → Kafka for event-driven pipelines → Spark for distributed processing → Airflow for orchestration and scheduling Once these concepts feel natural, the advanced ecosystem starts making more sense. You begin thinking beyond individual pipelines and toward reliability, scale, governance, and real-time architecture: ��� Data governance and catalogs → Data observability → Kubernetes → CDC + Debezium → Iceberg / Delta Lake → Apache Flink The important part is the order. Learning Flink before understanding SQL will not make you a stronger data engineer. Learning Kubernetes before you can build and debug a pipeline will only create more confusion. Master the foundations. Add distributed systems. Then learn how to operate data platforms at scale. That is how the staircase becomes a career path. Which level are you currently at: Basic, Intermediate, or Advanced?
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Satyen Mehta liked thisSatyen Mehta liked thisRAG is not one architecture anymore. 𝗕𝗲𝗰𝗼𝗺𝗲 𝗯𝗲𝘁𝘁𝗲𝗿 𝗮𝘁 𝗔𝗜 𝗶𝗻 𝗷𝘂𝘀𝘁 𝟭 𝗺𝗶𝗻𝘂𝘁𝗲 𝗮 𝗱𝗮𝘆. 𝗚𝗲𝘁 𝘁𝗵𝗲 𝗔𝗜 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿 𝘀𝗺𝗮𝗿𝘁 𝗹𝗲𝗮𝗱𝗲𝗿𝘀 𝗿𝗲𝗮𝗱. 𝗦𝗶𝗴𝗻 𝘂𝗽 𝗳𝗿𝗲𝗲 𝗻𝗼𝘄 → aiforleaders.com __________ The old version was simple. Vector search plus an LLM. For many teams, that was enough to build the first demo. But production systems are less forgiving. The problem is not only retrieval. It is retrieval design. A support bot, legal research assistant, analyst copilot, medical document reviewer, and enterprise knowledge tool do not all need the same pattern. They ask different questions. They carry different risk. They fail in different ways. That is why the RAG conversation is shifting. The better question is no longer: Which vector database should we use? The better question is: What kind of retrieval architecture does this use case need? This is where leaders can save weeks. Do not start by comparing tools. Start by naming the work the system must perform. Does it need exact lookup, relationship reasoning, tool planning, retrieval validation, or visual document understanding? That answer narrows the architecture fast. Hybrid RAG is for precision gaps. It combines dense vector search with sparse keyword search. Useful when semantic similarity misses exact terms, product names, IDs, policies, or technical language. GraphRAG is for relationship-heavy answers. It uses entities, connections, and graph structure. Useful when the answer depends on who, what, where, and how things relate. Agentic RAG is for multi-step retrieval. The agent plans which tools to use. It can search, inspect, decide, and keep going until it has enough confidence. Corrective RAG is for trust. It grades retrieved documents before relying on them. If retrieval is weak, it rewrites the query or falls back to another source. Multimodal RAG is for real enterprise files. It retrieves across text, images, charts, tables, decks, reports, invoices, and visual data. The mistake is treating RAG as a checkbox. That leads to brittle answers and expensive rewrites later. Treat RAG as an architecture decision. Start with the failure mode. Then choose the retrieval pattern. Better embeddings help. Better retrieval design matters more. Which architecture fits your next AI system?
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Satyen Mehta liked thisSatyen Mehta liked thisJumping out of a plane to mark the end of a career chapter? Possibly over the top. But, I had wanted to do it for a while, and it felt like a fitting way to mark the change. Four photos here say more than I can: a leap, LSEG’s iconic foyer, a final market close, and a fabulous but unplanned moment as veterans marched through the building. I will never really leave LSEG behind. The FTSE 100 will be quoted. IPOs will happen. I will think of the people behind them. It has been a privilege to contribute, in however small a way, to an institution at the heart of financial markets. I’m grateful for the time, the work, and the people. I’m especially grateful to Kevin Hunt who provided exceptional leadership, mentoring, and support. Thank you to everyone I worked with.
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Satyen Mehta liked thisSatyen Mehta liked thisYesterday, Monika Delekta-Ebbage and Phil Withey took to the stage at Google Cloud Summit, speaking about Building AI for Today and Tomorrow. During the session, they showcased the agent-to-agent capability we have been developing with Google Cloud. This is a London Market-focused protocol that enables AI agents to exchange information, clarify details, and confirm appetite in a more consistent and streamlined way. Alongside leaders from Google Cloud, they shared how we’re not just exploring what’s possible, but focusing on what delivers value for our customers today, while building for what comes next. A big part of that focus is reducing friction in underwriting: structuring and connecting data more effectively, enabling faster triage, and supporting better decisions without losing the expertise that underpins our business. With exciting plans in the pipeline, keep an eye out for more news on Hiscox London Market’s AI-enhanced capabilities. #AI #GoogleCloud #Insurance #Innovation #HiscoxLondonMarket
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Satyen Mehta liked thisSatyen Mehta liked thisJust wrapped up an incredible sales training in Salt Lake City! It was a fantastic experience, not just for the learning, but especially for the chance to meet and connect with so many great people from different departments across SAP Taulia A huge thank you to Lauren and Darcey Fletcher for putting together such a well-run and engaging training experience, your effort and energy really made it a success. Looking forward to applying what we covered and continuing to work with this amazing team. P.S. Visited the first ever KFC and finally met the Colonel… safe to say it did not disappoint 😆 🐓 #SalesTraining #SaltLakeCity #Teamwork #Sales SAP Taulia SAP
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Satyen Mehta liked thisSatyen Mehta liked thisHappy to share that I have completed Leadership with AI from ISB. It was a great journey with a set of brilliant people from various backgrounds, Weekly catch up with Milind who always made us look at “Why” instead of How & What of things & Learning/Sharpening our Business and Technology acumen. Nandu Nandkishore was probably the best mind-boggling session ever that could change the course of ones life. I would like to thank Sunil Wahi, Sanjiv Mahesh, Milind Naik, ISB course mates & my team for continuous support in achieving this milestone.
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Satyen Mehta liked thisSatyen Mehta liked thisLong-term Achievement Award And the winner is... Mandie Beitner. Congratulations Mandie #NSCGInterimAwards2025
Experience & Education
Licenses & Certifications
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Responsible AI in the Generative AI Era
Fractal Analytics
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Responsible AI in the Generative AI Era
Fractal Analytics
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Hindi
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Gujarati
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