Lead,Tech Product Owner

About Consilio

Job Summary:

The Enterprise Data Warehouse (EDW) Technical Product Owner is accountable for defining, prioritizing, and delivering EDW capabilities that create measurable value for internal clients and business stakeholders. This role establishes product direction, maintains a clear and actionable backlog, and serves as the primary decision-maker for scope and priority throughout the delivery lifecycle.

The Technical Product Owner partners closely with stakeholders, data engineers, developers, architects, project managers, and technical leads to translate strategic objectives and operational needs into product outcomes, user stories, acceptance criteria, and release plans. The role supports enterprise data solutions across relational databases, reporting platforms, ERP and CRM applications, middleware and iPaaS platforms, and proprietary systems. Success requires strong product judgment, technical fluency, stakeholder leadership, disciplined prioritization, clear communication, and the ability to make informed trade-offs among value, risk, effort, dependencies, and delivery timelines.

• Own the product vision, goals, roadmap, and delivery priorities for assigned data warehouse, reporting, and integration capabilities.
• Serve as the primary point of accountability for product scope, backlog quality, prioritization, and acceptance decisions.
• Partner with sponsors, stakeholders, subject matter experts, and technical teams to define desired outcomes, success measures, and product requirements.
• Create, refine, prioritize, and maintain the product backlog, including epics, features, user stories, technical enablement work, defects, and operational improvements.
• Develop clear user stories and acceptance criteria that communicate business value, expected behavior, data requirements, and quality expectations.
• Balance stakeholder demand, strategic alignment, technical dependencies, risk, capacity, and delivery effort when making priority and sequencing decisions.
• Lead backlog refinement and actively participate in sprint planning, reviews, demonstrations, release planning, and retrospectives.
• Provide timely product decisions and clarify scope, intent, and acceptance criteria so delivery teams can proceed without avoidable delays.
• Collaborate with engineering and architecture teams on solution options while maintaining accountability for product outcomes rather than prescribing implementation details.
• Coordinate dependencies across source systems, data integrations, enterprise data warehouse processes, semantic models, reports, and downstream consumers.
• Ensure data quality, security, privacy, governance, auditability, and supportability considerations are represented in product priorities and acceptance criteria.
• Engage stakeholders throughout delivery, communicate roadmap and release expectations, and manage changes to scope or priority transparently.
• Coordinate user acceptance testing by defining expected outcomes, identifying appropriate participants, reviewing results, and determining readiness for release.
• Accept or reject completed work based on agreed acceptance criteria and product quality expectations.
• Monitor production feedback, adoption, defects, support trends, and changing business needs to guide continuous product improvement.
• Identify and escalate delivery risks, unresolved dependencies, resource constraints, and decisions requiring leadership attention.
• Maintain product documentation and provide release communication, knowledge transfer, and training support as needed.

• Bachelor's degree in Computer Science, Information Systems, Mathematics, Engineering, Business, or equivalent relevant experience.
• Experience serving as a Product Owner, Technical Product Owner, Product Manager, or similar role for data, or analytics products.
• Demonstrated experience owning and prioritizing a product backlog and writing epics, user stories, and acceptance criteria.
• Working knowledge of Agile and Scrum practices, including backlog refinement, sprint planning, reviews, and release planning.
• Experience working with relational databases such as Microsoft SQL Server, Oracle, or equivalent platforms, including a practical understanding of SQL and data structures.
• Experience collaborating with technical teams delivering data warehouse, reporting, or data pipeline solutions.
• Experience using Jira or an equivalent product planning and work management platform.
• Strong stakeholder management, facilitation, negotiation, decision-making, and written and verbal communication skills.
• Ability to understand technical concepts, evaluate delivery trade-offs, and communicate effectively with both technical and non-technical audiences.
• Experience defining product outcomes, acceptance measures, and release readiness.

Preferred Experience:

• Knowledge of enterprise data warehouse architecture, dimensional modeling, ETL or ELT patterns, data quality, metadata, and data governance.
• Experience with Microsoft SQL Server, SSIS, SSAS, Power BI, Python-based data pipelines, or comparable data engineering and analytics technologies.
• Experience with Salesforce, NetSuite, ServiceNow, SnapLogic, or similar enterprise applications and integration platforms.
• Experience managing products that ingest data from multiple source systems and serve reporting, analytics, and operational use cases.
• Knowledge of software development lifecycle practices, test planning, production support, and release management.
• Project management experience or experience coordinating cross-team initiatives and dependencies.
• Experience in eDiscovery or legal technology is preferred but not required.
• Proficiency with Microsoft 365 products, including Power BI, Excel, OneNote, and Teams.

Core Competencies:

• Product ownership and accountability
• Roadmap and backlog management
• Value-based prioritization and trade-off decisions
• Technical and data fluency
• Stakeholder alignment and expectation management
• Agile delivery leadership
• Clear written and verbal communication
• Risk, dependency, and release management
• Analytical problem-solving and continuous improvement

Work Model

• 3 days Work from Office
• 2 days Work from Home

Shift Timing

• 7:00 PM to 4:00 AM night shift