2 Datafabric Jobs

Key Responsibilities: Work closely with clients to understand their business requirements and design data solutions that meet their needs. Develop and implement end-to-end data solutions that include data ingestion, data storage, data processing, and data visualization components. Design and implement data architectures that are scalable, secure, and compliant with industry standards. Work with data engineers, data analysts, and other stakeholders to ensure the successful delivery of data solutions. Participate in presales activities, including solution design, proposal creation, and client presentations. Act as a technical liaison between the client and our internal teams, providing technical guidance and expertise throughout the project lifecycle. Stay up-to-date with industry trends and emerging technologies related to data architecture and engineering. Develop and maintain relationships with clients to ensure their ongoing satisfaction and identify opportunities for additional business. Understands Entire End to End AI Life Cycle starting from Ingestion to Inferencing along with Operations. Exposure to Gen AI Emerging technologies. Exposure to Kubernetes Platform and hands on deploying and containorizing Applications. Good Knowledge on Data Governance, data warehousing and data modelling. Requirements: Bachelors or Masters degree in Computer Science, Data Science, or related field. 10+ years of experience as a Data Solution Architect, with a proven track record of designing and implementing end-to-end data solutions. Strong technical background in data architecture, data engineering, and data management. Extensive experience on working with any of the hadoop flavours preferably Data Fabric. Experience with presales activities such as solution design, proposal creation, and client presentations. Familiarity with cloud-based data platforms (e.g., AWS, Azure, Google Cloud) and related technologies such as data warehousing, data lakes, and data streaming. Experience with Kubernetes and Gen AI tools and tech stack. Excellent communication and interpersonal skills, with the ability to effectively communicate technical concepts to both technical and non-technical audiences. Strong problem-solving skills, with the ability to analyze complex data systems and identify areas for improvement. Strong project management skills, with the ability to manage multiple projects simultaneously and prioritize tasks effectively. Tools and Tech Stack: Data Architecture and Engineering: Hadoop Ecosystem: Preferred: Cloudera Data Platform (CDP) or Data Fabric. Tools: HDFS, Hive, Spark, HBase, Oozie. Data Warehousing: Cloud-based: Azure Synapse, Amazon Redshift, Google Big Query, Snowflake, Azure Synapsis and Azure Data Bricks On-premises: Teradata, Vertica Data Integration and ETL Tools: Apache NiFi, Talend, Informatica, Azure Data Factory, Glue. Cloud Platforms: Azure (preferred for its Data Services and Synapse integration), AWS, or GCP. Cloud-native Components: Data Lakes: Azure Data Lake Storage, AWS S3, or Google Cloud Storage. Data Streaming: Apache Kafka, Azure Event Hubs, AWS Kinesis. HPE Platforms: Data Fabric, AI Essentials or Unified Analytics, HPE MLDM and HPE MLDE AI and Gen AI Technologies: AI Lifecycle Management: MLOps: MLflow, KubeFlow, Azure ML, or SageMaker, Ray Inference tools: TensorFlow Serving, K Serve, Seldon Generative AI: Frameworks: Hugging Face Transformers, LangChain. Tools: OpenAI API (e.g., GPT-4) Orchestration and Deployment: Kubernetes: Platforms: Azure Kubernetes Service (AKS) or Amazon EKS or Google Kubernetes Engine (GKE) or Open Source K8 Tools: Helm CI/CD for Data Pipelines and Applications: Jenkins, GitHub Actions, GitLab CI, or Azure DevOps

Introduction A Data and AI Technology Sales Engineer role (what we internally call a, Brand Technical Specialist) within IBMs zStack brand means accelerating enterprises success by improving their ability to understand their data. It means providing solutions that enable people across organizations, in multiple roles, the ability to turn data into actionable insights without having to wait for IT. And it means solutioning and selling multi-award winning software deployed on IBM z/LinuxONE platform, and world-class design practices that enables business analysts to ask new questions. The answers to which are literally shaping the future and changing the world. Excellent onboarding and an industry leading learning culture will set you up for positive impact and success, whilst ongoing development will advance your career through an upward trajectory. Our sales environment is collaborative and experiential. Part of a team, youll be surrounded by bright minds and keen co-creators - always willing to help and be helped - as you apply passion to work that will compel our clients to invest in IBMs products and services. Your role and responsibilities Applying excellent communication and empathy, youll act as a trusted strategic advisor to some of the worlds most transformational enterprises and culturally influential brands, as they rely on your expertise and our technology to solve some of their hardest problems. With your focus on the front-end of the solution lifecycle, youll be a master at listening to stakeholders, grasping their business challenges and requirements, and forming more detailed definitions of new architectural structures that will make up their best-fit, value adding solutions. Were committed to success. In this role, your achievements will drive your career, team, and clients to thrive. A typical day may involve: Understanding client needs and aligning them with IBM Z solutions. Creating effective end-to-end architecture using IBM Z. Ensuring architectural viability and conducting assessments. Identifying and resolving project risks and conflicts. Your primary responsibilities will include: - Client Strategy Design: Creating client strategies for Data & AI infrastructure around the IBM z and LinuxONE platform - Solution Definition: Defining IBM Data & AI solutions that constitute functionalities such as Data Integration (ETL), Data Store (DB2, Oracle, MySql) and Data Science (Watson studio, Watson ML) leveraging the strengths of the IBM z and LinuxONE platform - Providing proof of concepts and simplifying complex topics for meeting clients business requirements in the area of data platform modernization and analytics. - Credibility Building: Establishing credibility and trust to facilitate architecture and solution benefits to drive revenue and technical business objectives. Required education Bachelors Degree Required technical and professional expertise Required Professional and Technical Expertise : - Minimum 8-14 years of experience in Data and AI technologies which should include infrastructure for Analytics & Advance Analytics solutions like Datalake, Data Warehouse, Business Analytics, AI, GenAI & Datafabric - Experiential selling including co-creation and hands-on technical sales methods such as: demos, custom demos, Proofs of concept, Minimum Viable Products (MVPs) or other technical proofs Build deep brand (Data & AI) expertise to assist partners to deliver PoX (Custom Demo, PoC, MVP, etc.) to progress opportunities. Identifying partners with skills, expertise, and experience Exceptional interpersonal and communication skills, and an ability to collaborate effectively with Ecosystem Partners, clients and sales professionals. Understanding of areas of Governance Risk and Controls is a bonus. Experience in AI Landscape and technologies at work across Banking/Finance Know how and technical capabilities and working experience on similar Data AI Products like Cloudera, Teradata, Oracle, Informatica, SAS, etc Preferred technical and professional experience - Knowledge of IBM Z and how it fits in the Digital Transformation (training in IBMs Z product will be provided)