Company Name:-
Splunk

Job Location:-
Seattle, WA 98103 (Green Lake – Wallingford area)

Job Summary:-
Job detailsJob TypeFull-timeFull Job DescriptionJoin us as we pursue our disruptive new vision to make machine data accessible, usable and valuable to everyone.

We are a company filled with people who are passionate about our product and seek to deliver the best experience for our customers.

At Splunk, we’re committed to our work, customers, having fun and most importantly to each other’s success.

Learn more about Splunk careers and how you can become a part of our journey!
As part of Splunk’s R&D team, the Data Science Organization is passionate about providing quantitative analytics and evidence to inform business decisions.

We partner with cross-functional business stakeholders to identify and address critical business questions and use data, analytical methods, and modeling to translate quantitative assessments into actionable insights.

Analyses inform business challenges such as guiding product roadmaps, streamlining engineering development lifecycles, and accelerating customer adoption and utilization trends.

We are seeking a Principal Data Architect who is passionate about creating the data and analytical platforms and infrastructure to support solving practical business questions with data-driven analytics.

Role:
As a Principal Data Architect, you will serve as the technical leader for creating and designing the data management and experimentation framework for the Data Science Organization.

You will translate business needs into requirements in collaboration with engineering, product management, IT, and other stakeholders to create the collaborative and secure environment for data, tools, and infrastructure to streamline data access, analysis and presentation.

You will be instrumental in architecting the infrastructure that moves and translates data to enable the analytical experiments, models, reports, and dashboards that inform business critical decisions.

Responsibilities:
Create the vision to build and evolve the team’s data infrastructure and tools.

Serve as the technical lead for the design, building, and launching of new data models and data pipelines.

Ensure production quality methods to retrieve, condition, validate, synthesize, and manipulate data.

Continuously evolve and improve the data arc

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