Data Team Product Owner (Remote - USA)

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Job description

Overview:
About Hexagon
Hexagon is a global leader in sensor, software and autonomous solutions. We are putting data to work to boost efficiency, productivity, and quality across industrial, manufacturing, infrastructure, safety, and mobility applications. Our technologies are shaping urban and production ecosystems to become increasingly connected and autonomous - ensuring a scalable, sustainable future.

empowers its clients to transform unstructured information into a smart digital asset to visualize, build, and manage structures and facilities of all complexities, ensuring safe and efficient operation throughout the entire lifecycle.

Hexagon (Nasdaq Stockholm: HEXA B) has approximately 21,000 employees in 50 countries and net sales of approximately 3.8bn EUR. Learn more at and follow us .

© 2021 Hexagon AB and/or its subsidiaries and affiliates. All rights reserved.

Responsibilities:
The Data Team Product Owner will act as a product owner and project manager in the areas of Big Data and data analytics. Responsibilities will include working with analytics team members from various business functions to understand the data needs across the organization. The product owner will be responsible for managing the backlog of data needs for a team that develops, customizes, and supports data solutions. Technologies involved include Azure Event Hub, Data Factory, Stream Analytics, Application Insights, Data Lake Store, DataBricks, Azure SQL Database and Data Warehouse, Informatica, Tableau, and Salesforce Einstein Analytics.

The individual will help define a Big Data strategy primarily using Microsoft cloud technologies. This individual will help define the direction of solutions for telemetry collection, data lake storage, and data warehousing needs. The individual will also assist other visualization teams as they consume data and analytics produced by the data team.

The Data Team Product Owner will also lead a cross-functional Analytics governance committee that defines the analytics strategy for the PPM organization. The individual will work executives, managers, product owners, sales, other internal users, and even customers to determine their analytic needs and translate into a product roadmap and backlog. The end goal is to produce clear and compelling information to stakeholders that will impact business performance improvements. The scope of data needs will expand as a data driven culture grows throughout the organization.

Responsibilities

Work with various stakeholders to define a realistic project roadmap

Communicate roadmap, risks, and status to various stakeholders including C-level executives

Define and prioritize epics of work, working with the technical team to decompose those into stories

Manage and prioritize a backlog of user stories tracked against epics and ultimately the project roadmap

Adjust the backlog to meet schedule based on factors such as team estimates, projected velocity, and business requirements for delivery

Qualifications:
A Bachelor's Degree in Computer Science, Information Systems, Mathematics or related field with 3-5+ years of experience is required.

3-5+ years of experience as an Agile Product Owner using Scrum processes in a DevOps culture

Multi-disciplinary background in data and analytics

Experience working with large and complex projects

Strong communication and interpersonal skills in order to work directly with consumers and peers

Experience working with stakeholders to define a realistic project roadmap

Experience communicating roadmap, risks, and status to various stakeholders including C-level executives

Experience working with various data consumers to understand needs

Experience with techniques for scheduling stories to maximize value delivery, such as prioritization, defining a product MVP, splitting/refining epics, and descoping

Experience with relational as well as non-relational databases

Preferred

Scrum certification for product ownership

Experience with Spark or another similar technology for processing big data

Experience with the following technologies: Azure Data Lake, Databricks (including Databricks SQL and Delta Lake), Tableau, Salesforce Einstein Analytics, Microsoft SQL Server, Informatica Cloud or Collibra

Experience with build and deployment automation and a DevOps culture

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