Senior Technical Architect, Data Engineering

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. Enterprises are modernising data platforms and processes at a growing rate to meet the demands of their customers. A majority of this journey requires not just technical expertise but also the ability to drive predictability, and manage complexity. Snowflake’s Professional Services Organisation offers our customers a market-leading set of technical capabilities as well as best practices for modernisation based on experienced leadership. Our portfolio of modernisation solutions spans data migrations, validation, application development, data sharing, lakehouse implementations, data science, and AI. As a Solutions Architect in our team, you will be responsible for delivering exceptional outcomes for our teams and customers during our modernisation projects, with a focus on modern data architectures including lakehouses and streaming data. You will engage with customers to migrate from legacy data platforms, including those based on Cloudera, and build modern data pipelines and lakehouse solutions on Snowflake where customers can then leverage downstream AI and Machine Learning solutions. You will act as the technical lead and expert for our customers throughout this process, guiding customers through decision paths to achieve impactful outcomes and thoughtfully use AI to augment their business In addition to customer engagements, you will work with our internal team to provide requirements for our Snowconvert utility, based on project experiences. This ensures that our tooling is continuously improved based on our implementation experience. This role will report to the Director of specialised Workload Solutions team within the PS&T organization at Snowflake. KEY RESPONSIBILITIES: Delivery Be well-versed in migrations of applications, code, and data onto cloud platforms - and how to lead design of the subsequent services onto Snowflake, including lakehouse architectures using Iceberg Have the ability to outline the architecture of Spark, Scala, and Cloudera environments. Guide customers on architecting and building data engineering pipelines on Snowflake, including streaming data ingestion and processing Design and implement data ingestion and transformation pipelines using Apache NiFi. Architect and implement Iceberg based lakehouse solutions on Snowflake Run workshops and design sessions with stakeholders and customers Troubleshoot migration and implementation issues Create repeatable processes and documentation as a result of customer engagement. Scripting using Python and shell scripts for ETL workflow Develop best practices, including ensuring knowledge transfer so that customers are properly enabled and are able to extend the capabilities of Snowflake on their own Provide guidance on how to resolve customer-specific technical challenges Outline a testing strategy and plan Optimize Snowflake for performance and cost Design and implement solutions for streaming data ingestion and processing Product Strategy Communicate requirements for capabilities on Snowpark conversion for Scala/Python and Spark based back end software modules Communicate requirements for design and development of back end big data frameworks for enhancements to our Snowpark platform Weigh in on and develop frameworks for Distributed Computing, Apache Spark, PySpar