Chief Data Architecture Expert

A Senior Data Architect is a leading member of our team.

The role involves working on exciting distributed data business problems at private and public sector organizations. The candidate will engage in early stage conversations with customer prospects through to production implementations at large multi-cluster customers. They will lead, evangelize, and collaboratively work with customers, advising them on the rollout of reference enterprise data architectures, identify and drive development of use cases and analyze as well as recommend solutions to distributed computing challenges.

• Evangelize, motivate, and enable customers on their Enterprise Data Cloud journey.
• Participate in pre- and post-sales processes, helping sales, professional services management, and product teams interpret customer use cases.
• Assist customers in defining their data strategy, use case success criteria, and frameworks to deliver successful implementations.
• Design and implement Enterprise Data Cloud architectures and configurations for customers.
• Identify and grow professional services engagements and support subscriptions through clear demonstration of value.
• Design, create, and recommend standard best practices design patterns for distributed data pipelines and analytical computing architectures.
• Plan and deliver presentations and workshops to customer/internal stakeholders.
• Mentor junior consultants and architects.
• Help define our approach and screen candidates in the technical hiring process.
• Write and produce technical documentation, blogs, and knowledge base articles.

As a Senior Data Architect, you will:

● Use deep domain, wide technical, and business knowledge to assist customers in defining their data strategy, use case success criteria, and frameworks to deliver successful implementations.

● Design and implement Enterprise Data Cloud architectures and configurations for customers.

● Identify and grow professional services engagements and support subscriptions through the clear demonstration of the value we bring to our customers.

● Design, create, and recommend standard best practices design patterns for distributed data pipelines and analytical computing architectures.

● Plan and deliver presentations and workshops to customer/internal stakeholders.

● Mentor junior consultants and architects.

● Help define our approach and screen candidates in the technical hiring process.

● Write and produce technical documentation, blogs, and knowledge base articles.

Benefits include a strong business understanding of how Cloudera technologies solve real-world business problems and an appreciation of the commercial business cases that drive customer data platform initiatives. Experience managing project delivery and leading a technical team are also required.

• Extensive customer-facing/consulting experience interacting with large-scale distributed data/computing solutions.
• Strong business understanding of how Cloudera technologies solve real-world business problems.
• Appreciation of the commercial business cases that drive customer data platform initiatives.
• Experience managing project delivery and leading a technical team.
• Strong experience designing, architecting, and implementing software solutions in an enterprise Linux environment.
• Strong experience with Hadoop or related technologies, including deployment and administration.
• Excellent communication skills and experience with public speaking.
• Proven knowledge of big data/analytical use cases and best practice approaches to implement solutions.
• Strong experience with Cloud Platforms (i.e., AWS, Azure, Google Cloud).
• Experience with open-source ecosystem programming languages (i.e., Python, Java, Scala, Spark, etc.).
• Knowledge of the data management ecosystem, including concepts of data warehousing, ETL, data integration, etc.
• Experience designing frameworks for implementing data transformation and processing solutions on Hadoop or related technologies.
• Strong understanding of authentication and authorization configuration for Hadoop-based distributed systems.
• Deep knowledge of the Data/Big Data business domain.
• Familiarity with BI tools and Data Science notebooks such as Cloudera Data Science Workbench, Apache Zeppelin, Jupyter, IBM Watson Studio, etc.
• Knowledge of scripting tools such as bash shell scripts, Python, or Perl.
• Familiarity with DevOps methodology and toolsets and automation experience with Chef, Puppet, Ansible, or Jenkins.

You may also have related industry experience and relevant architecture certifications. Experience implementing machine learning algorithms using R or TensorFlow and a deep understanding of statistical methods are also beneficial.