The job details are as follows:OCLC is seeking a Senior Technical Manager to lead our Analytics & Data Engineering team supporting WMS reporting and our internal data warehouse and ETL ecosystem. This is a transformative role focused on building a high-performing team, strengthening accountability and delivery predictability, and guiding our modernization from on-prem data/compute to a Snowflake-based platform.
You will manage a team of analytics engineers, ETL engineers, and developers responsible for Power BI reporting, dbt-based transformations, and the data pipelines and practices that ensure trusted, well-governed analytics across the organization.
Major Responsibilities:People Leadership & Team Development- Lead, coach, and develop a large team setting clear expectations, create accountability, and ensure consistent follow-through on commitments.
- Establish a culture of ownership, quality, collaboration, and continuous improvement; provide timely feedback and address performance issues directly.
- Drive career development through growth plans, mentoring, skills development, and opportunities for technical leadership across reporting and data engineering work.
Delivery Leadership & Execution Management- Own delivery outcomes for reporting, data warehouse, and ETL initiatives—ensuring work is planned, executed, and completed with high quality and predictable timelines.
- Implement strong agile practices: healthy backlog management, multi-sprint planning, quarterly roadmap alignment, dependency/risk tracking, and stakeholder-ready status communication.
- Balance roadmap delivery with operational support, defect reduction, and technical debt, using clear prioritization and capacity planning.
- Analytics Platform Strategy, Governance & Cost Management (Snowflake and Cloud Consumption)
- Lead the team’s contribution to OCLC’s migration from on-prem to Snowflake, including operating model changes, standards, and adoption of best practices.
- Establish and enforce governance practices for analytics data: access controls, data classification, documentation, lineage, and data quality expectations.
- Partner with architecture, security, and finance stakeholders to manage Snowflake and Azure PowerBI cost drivers (compute/storage), implement guardrails, and drive optimization (warehouse sizing, scheduling, monitoring, and usage patterns).
Technical Oversight (hands-on optional; leadership required)- Provide technical direction and review for dbt modeling patterns, testing, orchestration approaches, and deployment practices.
- Ensure Power BI reporting is scalable and supportable through shared datasets/semantic consistency, metric definitions, and reusable data products.
- Improve operational excellence through monitoring/alerting, incident response practices, and root-cause remediation for pipeline and reporting issues.
- Development using React and other modern tools for our front end applications.
Minimum Qualifications:
- Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related field (or equivalent experience).
- 8+ years of experience in analytics engineering, data engineering, BI/reporting, or data platform engineering.
- 5+ years of people management experience leading technical teams, including coaching, performance management, and team development.
- Demonstrated success improving delivery predictability and accountability for technical teams (planning beyond a single sprint, driving work to completion).
- Strong knowledge of data warehousing concepts (dimensional modeling, ELT/ETL patterns, data quality, orchestration).
- Experience supporting business intelligence/reporting programs with stakeholder-facing prioritization and communication.
Desired Qualifications:
- Experience with Snowflake including governance and cost optimization.
- Strong experience with dbt (modeling conventions, testing, documentation, environments, CI/CD).
- Strong experience with Power BI (semantic modeling, datasets, performance considerations, governance).
- Experience modernizing analytics platforms and migrating from on-prem to cloud data platforms.
- Familiarity with data security and privacy practices in analytics environments
Working Conditions: Normal office environment.
