Data Engineering Manager

Location/Remote: Hybrid Remote in Cleveland, OH 44143 (i.e., 4 days onsite/week)Employment Type: Direct Hire / Permanent / Full-timeCompensation: up to $170k salary/year + Profit Sharing = up to $190k total compensation/yearBenefits: 100% company paid medical (for you + your family), dental, vision, LTD/STD, HSA/FSA, term life, supplemental health insurances (e.g., Aflac), 12-weeks paid maternity leave, 401(k) + 3% company match, Unlimited PTOThis senior leadership role owns the architecture, reliability, and evolution of an enterprise data platform that powers analytics and AI/ML use cases. Success is measured by building a scalable, cost-effective cloud data ecosystem, raising engineering standards and data quality across the organization, and growing a high-performing data engineering team. You will partner closely with technical and business leaders to align platform investments to measurable outcomes.Responsibilities:Own the enterprise data engineering platform strategy, including target architecture, multi-quarter roadmap, and prioritized delivery plans aligned to business goals.Lead the design and scaling of data lakes, data warehouses, batch/streaming pipelines, and large-scale data integration patterns to support enterprise reporting and advanced analytics.Establish engineering standards for data modeling, pipeline development, testing, CI/CD, observability, documentation, and operational readiness across the data platform.Drive cloud architecture decisions (preferably Azure) across storage, compute, security, and networking to improve reliability, performance, and maintainability.Implement and continuously improve data governance and data-quality frameworks, including data lineage, metadata management, validation rules, SLAs, and issue triage processes.Manage platform reliability by defining SLOs, monitoring and alerting, incident response practices, and post-incident reviews that lead to concrete preventive actions.Optimize platform costs by creating chargeback/showback visibility, right-sizing workloads, reducing waste, and setting guardrails for efficient resource usage.Lead, hire, and mentor senior data engineers and technical leads; set clear expectations, coach performance, and build succession plans for critical roles.Partner with Analytics, AI/ML, Product, and executive stakeholders to translate needs into platform capabilities, tradeoffs, and delivery milestones.Govern architecture reviews and technical decision-making to ensure solutions are secure, scalable, and consistent with enterprise standards and long-term direction.Required Skills:10+ years of experience in data engineering, data architecture, or related disciplines, including 5+ years leading senior engineers or technical teams and mentoring high-performing engineering organizations.Proven experience architecting, building, and scaling enterprise data platforms, including data lakes, data warehouses, pipelines, streaming architectures, and large-scale data integration environments.Strong cloud data engineering experience (preferably Azure) with hands-on architectural knowledge of platforms/technologies such as Azure SQL, Microsoft Fabric, Databricks, Snowflake, Kafka, or comparable tools.Experience establishing enterprise data governance and data-quality frameworks, engineering standards, platform reliability practices, scalability approaches, and cost optimization across complex data environments.Demonstrated ability to set data engineering strategy, influence technical and business stakeholders, and partner effectively across Analytics, AI/ML, Product, and executive leadership.Preferred Skills:Experience leading data platform, system, or data-integration efforts tied to mergers and acquisitions, including harmonizing data models and consolidating pipelines and tooling.Background in IT Services, Managed Services, or similar enterprise technology environments, particularly supporting ERP, ServiceNow, or supply-chain data ecosystems.Relevant cloud or data-platform certifications (Azure, AWS, GCP, or equivalent advanced credentials).