IT Senior Data Product Owner

Atmus•Nashville, TN

2d•Hybrid

About The Position

The IT Senior Data Product Owner is accountable for the value, quality, and adoption of an assigned portfolio of enterprise data products. The role bridges business stakeholders and the Data & Analytics delivery team, partnering with functions including Sales, Marketing, Customer Service, Supply Chain, Finance, and IT to understand decision-making needs and translate them into trusted, governed, reusable data assets. The role owns data product vision, roadmaps, release plans, and backlogs, defining what is built and why, setting acceptance criteria and data quality expectations, and ensuring products are adopted to improve business outcomes. Products may include curated data sets, semantic models, certified KPIs and metrics, dashboards, and data services, built on Snowflake and Tableau and sourced from systems including Oracle EBS and Fusion, Salesforce, and ServiceNow. The role supports commercial, customer experience, and AI roadmaps, including integration of data from newly acquired businesses. This is a hands-on role involving business workshops, user-story development, SQL-based source-data profiling, and dashboard validation. The position is based in Nashville, Tennessee, with a hybrid schedule of three days in the office and two remote, and less than 10% travel.

Requirements

Bachelor’s degree in a relevant technical or business discipline.
At least 5 years of experience in data analysis, business analysis, or data and analytics roles.
Experience delivering enterprise data products, data warehouses, or analytics solutions used across multiple business functions.
Strong understanding of business processes and related data, including Lead-to-Cash or Order-to-Cash, customer and product master data, sales and customer service performance, supply chain and inventory, and financial reporting.
Strong SQL skills for data profiling, analysis, and validation.
Hands-on experience with cloud data platforms and BI tools; Snowflake and Tableau are preferred, while Databricks and Power BI are acceptable.
Experience with data modeling concepts, including dimensional models and semantic layers.
Experience with data quality, profiling, and statistical process control techniques.
Experience with data catalog, metadata, and lineage tools.
Experience with ERP and CRM data structures, including Oracle EBS/Fusion and Salesforce.
Experience with APIs and integration concepts.
Experience with Agile and product delivery methodologies.
Strong understanding of data governance and master data concepts.
Excellent relationship-building, interpersonal, analytical, problem-solving, and facilitation skills; strong business acumen and customer focus.
Ability to present, negotiate, and influence business stakeholders and communicate effectively in writing and presentations to professional and executive audiences.
Experience working in matrix environments and operating effectively in global, cross-cultural environments.

Nice To Haves

Advanced degree.
Experience in manufacturing, distribution, industrial, or consumer products industries.
Agile product certification such as CSPO or PSPO, or Snowflake, Tableau, or data governance certification such as CDMP.
Experience preparing data for AI/LLM use cases such as search, recommendations, or agents, or applying machine learning to data quality.
Familiarity with Tableau Pulse, Salesforce CRM Analytics, or MuleSoft.
Experience integrating data from acquired businesses or supporting multi-region operations.
Domain experience in filtration, automotive, or heavy-duty aftermarket parts.

Responsibilities

Build relationships with business leaders and function-aligned Business Analysts and Business Solutions Managers to understand decisions, business questions, and success KPIs.
Align data product priorities with business objectives, enterprise data strategy, and domain application roadmaps; serve as the clear point of communication on what data is being built and why.
Own the vision, roadmap, and release plan for assigned data products, including their purpose, consumers, scope, and success measures.
Own and groom the data product backlog, prioritizing transparently across business value, effort, data readiness, and dependencies.
Decompose initiatives into Epics, Features, and User Stories with acceptance criteria, data quality thresholds, and a shared definition of done.
Track and report product adoption, usage, value delivered, and quality metrics to senior leadership; identify opportunities to consolidate redundant reports and data sets into certified reusable products.
Elicit, document, validate, and prioritize data requirements, including business definitions, metric logic, granularity, refresh frequency, history, and access needs.
Lead KPI and metric definition workshops and certify agreed enterprise metrics; map source-to-target flows and business rules, identify data gaps, and present options and trade-offs for ambiguous business questions.
Plan and lead data validation and user acceptance testing, including reconciliation against source systems.
Profile and analyze source and curated data to identify quality, coherency, and integration issues and reduce redundancy.
Define data quality rules, cleansing methods, thresholds, and service levels with data owners and stewards; apply statistical process controls to monitor quality over time.
Maintain data catalog entries, glossary terms, definitions, lineage, ownership, classification, usage guidance, and metadata quality for assigned products.
Partner with data owners, stewards, and IT Governance to incorporate quality findings into governance processes, controls, and remediation plans; ensure compliance with security, privacy, access-control, and regulatory requirements.
Improve customer, product, and other master-data quality and governance processes in partnership with the business.
Partner with data engineers, architects, and integration teams on Snowflake pipelines, data models, and semantic layers.
Write and run SQL to profile, explore, and validate data, scope work, write precise tickets, and assess estimates.
Build, configure, or validate Tableau dashboards and metrics, including Tableau Pulse, for assigned products.
Understand source data structures and integration patterns across Oracle EBS and Fusion, Salesforce, ServiceNow, and MuleSoft to diagnose issues at source.
Evaluate and apply machine-learning and AI-assisted tools to improve data quality, metadata, and data discovery; ensure products are documented, governed, trustworthy, and AI-ready in line with company AI governance standards.
Participate in or lead medium-to-large data and analytics initiatives; assist with planning, prioritization, risk management, and stakeholder communications.
Support organizational change management, training, and user adoption, including retirement of legacy reports; promote standardized processes, governance, and documentation.
Coordinate handoffs among business stakeholders, Business Solutions, Data & Analytics, integration, and ERP teams, and manage dependencies such as source-system readiness and acquisition-data integration.
Maintain documentation of decisions, business rules, controls, and processes, and create training materials.
Coach, mentor, and review less experienced team members and guide problem resolution.
Present to, negotiate with, and influence business stakeholders, including professional and executive-level audiences; collaborate effectively in matrixed and global, cross-cultural environments.