Data Strategist (Data Warehouse & Reporting)

For years, Stream Data Centers has been a trusted partner in providing world-class data center solutions. With a focus on sustainable, secure, and reliable infrastructure, Stream empowers businesses to scale their digital operations while prioritizing environmental and social responsibility. 

Stream Data Centers continues to set new standards for innovation, operational excellence, and sustainability in the data center industry, having provided premium data center services since 1999. Now, with 90% of its inventory leased to Fortune 100 customers, the company has acquired, developed and managed more than 27 data center projects nationally, while leadership has remained consistent for over two decades. 

From site selection to data center construction and operations, Stream develops wholesale colocation capacity and build-to-suit facilities for hyperscale and enterprise users in major markets across the United States. Additionally, Stream sources and develops low-risk land sites for optimum data center development and provides energy procurement services with a focus on reducing market risk and providing low-cost renewable energy options.

Information Technology Department: 

Stream’s IT team delivers modern, secure technology solutions that power our global operations. We combine proactive management, rigorous cybersecurity, and agile software development to drive business growth. By aligning technology strategy with business goals, we keep Stream at the forefront of innovation and operational excellence. 

The Role: 

The Data Strategist (Data Warehouse & Reporting) owns Stream’s enterprise understanding of data: what data we have, where it lives, how it is acquired and transformed into the Data Warehouse (DW), and how it is consumed through reporting, analytics, and downstream systems. You will partner with Business leaders, Data Engineering, Application teams, and IT to define a clear, trusted data ecosystem that enables consistent decision-making across the organization. 

You will establish and maintain data domain definitions, business glossaries, and end-to-end lineage from source systems through ingestion, modeling, and dashboards. Success requires strong communication skills, a systems mindset, and the ability to translate business questions into governed data products—while driving adoption of standards for data quality, documentation, and change management. 

Key Responsibilities: 

• Own the enterprise data inventory and strategy: Maintain an authoritative view of key data domains, systems of record, and critical data elements; define a roadmap for improving discoverability, governance, and reuse across the organization. 

• Document where data lives and how it is accessed: Develop and maintain a data catalog that clearly maps sources, schemas, tables, metrics, and owners; publish guidance on how to request, access, and use approved datasets. 

• Own end-to-end lineage into the DW: Define and keep current the lineage from source systems through ingestion, transformation, and dimensional/semantic models; ensure stakeholders understand “where the number comes from.” 

• Partner on data acquisition and integration: Work with Data Engineering and application owners to intake new sources into the DW (batch/stream), clarify business requirements, and validate that delivered datasets meet reporting and operational needs. 

• Define business metrics and a common glossary: Standardize KPI definitions, calculation logic, dimensional attributes, and naming conventions; resolve metric conflicts and drive adoption of a single source of truth for reporting. 

• Govern reporting usage and enable self-service: Align dashboards, datasets, and semantic models to approved definitions; establish guidance for certified datasets and reporting standards to reduce duplicated or inconsistent reporting. 

• Drive data quality and issue management: Define critical data quality checks, monitoring expectations, and triage processes; coordinate root-cause analysis across source owners and engineering teams and communicate impacts to stakeholders. 

• Lead change management for data and reports: Implement processes for schema changes, metric revisions, and dashboard updates; manage stakeholder communication, versioning, and release notes to prevent breaking changes. 

• Support governance, compliance, and security alignment: Collaborate with Security and Risk teams to ensure appropriate classification, retention, and access controls for data used in reporting; help maintain audit-ready documentation for key datasets and KPIs. 

• Document and train: Create and maintain data product documentation, lineage diagrams (where applicable), and reporting guides; deliver enablement sessions for analysts and business users to improve adoption and correct usage. 

• Act as the primary cross-functional data liaison: Facilitate alignment between business stakeholders and technical teams; prioritize data needs, clarify requirements, and communicate tradeoffs to leadership. 

• Drive continuous improvement in the data ecosystem: Evaluate and recommend practices and tooling for cataloging, lineage, semantic modeling, and reporting; identify opportunities to simplify pipelines, reduce redundancy, and improve trust in data. 

Success Metrics & KPIs:

• Data discoverability and clarity: High adoption of the data catalog and glossary; reduced time for teams to find the right dataset/definition; fewer recurring questions about metric meaning and sourcing. 

• Trusted lineage to the DW: Documented and current lineage for priority data products from source through DW and semantic models; fewer report discrepancies due to unclear transformations. 

• DW intake and data product delivery: Predictable onboarding of new sources and enhancements; clear requirements, acceptance criteria, and stakeholder sign-off with low rework. 

• Reporting consistency: Reduced duplication of dashboards and conflicting KPIs; increased use of certified datasets/semantic models; improved stakeholder confidence in executive reporting. 

• Data quality and governance outcomes: Measurable reduction in high-severity data issues and faster resolution times; improved completeness of documentation and audit-ready controls for key datasets. 

Basic Qualifications 

• Bachelor’s degree or equivalent combination of education and experience. 

• 7–10 years in data strategy, analytics, data governance, or data engineering/BI roles, with hands-on experience supporting a modern Data Warehouse and enterprise reporting. 

• Strong understanding of DW concepts (ingestion, transformation/ELT, dimensional modeling, semantic layers) and how those components support consistent, scalable reporting. 

• Demonstrated ability to define and operationalize business metrics, data definitions, and ownership models (data domains, stewardship) and to reconcile conflicting KPI logic across teams. 

• Working knowledge of SQL and data validation techniques; ability to partner with engineers on requirements, acceptance criteria, and root-cause analysis for data issues (coding-heavy role not required). 

• Experience with BI and reporting platforms (e.g., Power BI or similar) including semantic models, dataset governance, and best practices for reliable self-service reporting. 

• Experience with data cataloging, lineage documentation, or governance workflows; familiarity with metadata management concepts and tools is strongly preferred. 

• Comfort working in environments with security, privacy, and audit expectations; ability to produce clear documentation and support evidence for controls related to reporting and data access. 

• Excellent written and verbal communication; proven ability to influence cross-functional teams and mentor others. 

• Ability to work across multiple U.S. locations and travel to data center sites as needed; after-hours availability for high-priority identity incidents when required. 

Preferred Qualifications 

• Experience with Data Warehouse platforms (e.g., Microsoft Fabric/Snowflake/Azure Synapse/SQL Server or similar)
• Experience with ETL/ELT orchestration (e.g., ADF/dbt/Airflow or similar)
• Experience with Power BI (or comparable BI tool), SQL, Git-based workflows, data catalog/lineage tools (e.g., Purview/Collibra/Alation or similar)
• Familiarity with data quality tooling and ticketing/incident workflows 

• Health Care Plan (Medical, Dental & Vision)
• Retirement Plan (401k, IRA)
• Life Insurance (Basic, Voluntary & AD&D)
• Paid Time Off (Vacation, Sick & Public Holidays)
• Family Leave (Maternity, Paternity)
• Short Term & Long Term Disability
• Training & Development
• Wellness Resources

The pay range for this role is between $120,000 – 140,000 (base). Individual compensation packages are based on various factors unique to each candidate, including skill set, experience, qualifications, location, and other job-related reasons. Stream Data Centers offers annual bonus, benefits, flexible time off (vacation), 401k and a variety of other perks and benefits.

Stream is an equal-opportunity employer and does not discriminate on the basis of ethnicity, race, religion, sex, age, national origin, disability, military status, or any other reason prohibited by law. Note: Nothing in this job description restricts management’s right to assign or reassign duties and responsibilities to this job at any time.

Salary : $120,000 - $140,000