Consulting Data Architect

World Wide Technology•Denver, CO

4d•Remote

About The Position

The Consulting Data Architect designs and builds monitoring and observability data platforms using batch, real-time, and event-driven architectures. The role develops conceptual, logical, and physical data models for patterns such as star and Kimball modeling, across OLTP and OLAP technologies, with a focus on event insight, system and platform health, and IT Operations KPIs. It integrates tools such as LogicMonitor, ServiceNow, and BigPanda into designed platforms and works with data engineers as a subject-matter expert to build the systems designed. The architect engages customers during presales to understand requirements and deliver solutions, serves as a trusted strategic advisor on IT monitoring and observability, and advises on data processing frameworks and tools. The role supports clients ranging from Fortune 50 companies to startups, collaborates with application development teams, and contributes to WWT’s knowledge repository through proofs of concept and articles. It also supports business development efforts, standardizes tools, processes, and documentation, and provides thought leadership on IT Operations and data streaming through blog posts and speaking opportunities. The position includes coaching and mentoring peers as WWT’s data practice grows.

Requirements

Experience architecting, prototyping, and building data platforms using Apache Kafka, Neo4j, Splunk, Azure Event Hub, or similar technologies.
Experience designing and building streaming applications using frameworks such as Kafka Streams, Spark, and Apache Flink.
Ability to understand and configure data platforms for client needs, including performance, reliability, and security.
Experience architecting and creating data schemas according to best practices for data in motion.
Experience collaborating across disciplines such as Data Science, data warehousing and business intelligence, Operations, and application development, and integrating their tools and processes with streaming platforms.
Ability to present the value of data streaming platforms to audiences with differing levels of technical knowledge, from developers to CTOs.
Ability to understand, document, and diagram complex systems.
Experience with containerized applications and orchestration.
Experience with at least one traditional data warehousing technology, such as Teradata, Oracle, or SQL Server, and/or modern platforms such as AWS, Google Cloud Platform, or Azure.
Experience with at least one scripting language, such as Python, Java, or Scala.
Experience with SQL scripting, tuning, indexing, partitioning, data access patterns, and scaling strategies.
Experience with data integrations and processing for IT Operations event management and analysis.
Experience as a key contributor to developing an enterprise data warehouse.
Hands-on experience with at least one public cloud platform.
Passion and experience with architectures for complex software on one or more major public cloud platforms: AWS, Microsoft Azure, or Google Cloud Platform.
Detailed understanding of cloud-native concepts and tradeoffs.
History of leading teams technically or managerially to deliver working software that solves a business problem.
Software engineering background and strong skills in one or more major development languages, such as Java, C#, or Node.js, as well as familiarity with scripting languages and infrastructure-as-code deployment.
Self-motivated, principled problem solver with a strong attitude and willingness to own problems through resolution.

Nice To Haves

Knowledge of no-code tooling such as Apache NiFi, Informatica, and AWS Glue.
Knowledge of different Kafka offerings, such as Confluent Kafka Platform and Cloud, MSK, and Cloudera.
Experience operating and managing Kafka clusters at scale.
Experience with containerized applications and orchestration.

Responsibilities

Design monitoring and observability data platforms using batch, real-time, and event-driven architectures.
Create conceptual, logical, and physical data models for different modeling patterns and OLTP and OLAP technologies.
Integrate tools such as LogicMonitor, ServiceNow, and BigPanda into designed platforms.
Build designed systems and work with data engineers as a subject-matter expert.
Clearly present and communicate project results and issues to internal WWT teams.
Contribute proofs of concept and articles to WWT’s knowledge repository.
Work with the WWT business development team to support a sales solution architecture for a large business development services effort.
Design event-driven architectures with clients or WWT application development teams.
Engage customers during presales, understand their requirements, and deliver solutions.
Act as a strategic advisor on IT monitoring and observability.
Guide clients on when and how to use different data processing frameworks and tools.
Develop tools, processes, and documentation to standardize ways of working.
Provide thought leadership on IT Operations and data streaming technologies and architecture through blog posts and speaking opportunities.
Coach and mentor peers as the WWT data practice grows.