Product Manager, Business Systems & Data

Job Requisition ID #

Responsibilities:            

Plan, initiate, and manage information technology (IT) projects. Lead and guide the work of technical staff. Serve as liaison between business and technical aspects of projects. Plan project stages and assess business implications for each stage. Monitor progress to assure deadlines, standards, and cost targets are met. Develop data-driven products to gain insights into customer behavior and needs. Work with stakeholders to define objectives and create data-driven products. Utilize appropriate data sources to collect and analyze data. Gather feedback from stakeholders to improve data-driven products. Design and implement product roadmaps for data-driven products. Monitor product performance and suggest improvements. Collaborate with engineering and design teams to ensure product success. Assist with the development of new product ideas and strategies. Present product updates and insights to stakeholders. Drive the ACS Enterprise Data vision, strategy, and roadmap aligned with user needs and business priorities and objectives. Partner with data owners, data stewards, and data custodians to ensure that data-related business requirements are clearly defined, communicated, well understood, and considered as part of operational prioritization and planning. Align with Autodesk’s Enterprise Data governance strategy focused on ensuring data is collected, stored, enriched, and maintained according to industry-standard SLAs and SLOs. Facilitate developing and implementing data quality standards, data protection standards, and adoption requirements across the organization. Manage and control costs associated with collecting, managing, and sharing data while growing the value of the data to the organization. Define indicators of performance and quality metrics and ensure compliance with data related policies, standards, roles and responsibilities, and adoption requirements. Maximize the business impact and operational efficiencies of a proper data management practice. Exhibit strong relationship management skills to work with users and stakeholders across the organization. Working closely with Data Engineering groups and business groups on different software tools/ platforms such as snowflake data warehouse, Dbt, GitHub, looker, Salesforce CRM, Oracle NetSuite, and other software applications as needed. Embracing and enabling the best ways to adopt Agile methodology within the data engineering groups.  Must be available to work on projects at various, unanticipated sites throughout the United States. Telecommuting is permitted.

Minimum Requirements:

Master’s degree in Management Information Systems, Information Technology, or related field and three (3) years of experience in the job offered or in a IT/Data-related occupation-related occupation. Must be available to work on projects at various, unanticipated sites throughout the United States. Telecommuting is permitted.

Special Requirements:

Position requires at least two (2) years of experience in each of the following skills:

• Utilize the knowledge of enterprise data modeling concepts to collaborate with data architects, product owners, technical leads and create enterprise data modeling (conceptual/logical/physical data models), application-level data models and data lineage using ER studio Suite (data architect and business architect) & Visio tools

• Utilize the knowledge of ETL/integration using dell boomi, IICS (Informatica Intelligent cloud services), Microsoft Azure platforms-MS Azure SQL, ADF (Azure Data factory) & ADL (Azure Data Lake) Work with integration groups for recommending the right patterns.

• Utilize the knowledge of analytical reporting tools such as Power BI/Tableau/SSRS to support the end user teams

• Utilize data architecture to develop and promote corporate architecture best practices and standards.

• Utilize the knowledge of data architecture, data modeling skills to Design, testing, and deploying data models using the visual paradigm tool for data modeling and Jenkins server to run and deploy builds. Use shell scripts that automate the process of testing the data model objects.

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