What are the responsibilities and job description for the Analytics Engineer - Enterprise Analytics position at D&H Distributing?
Analytics Engineer – Enterprise Analytics
This is a fully remote position.
D&H is growing! Join 100 year old Employee-Owned technology distributor, offering end-to-end solutions for today's resellers, retailers, and the clients they serve across the SMB and Consumer markets.
We are seeking an Analytics Engineer – Enterprise Analytics for our Data Science & Insights Department. This position is responsible for developing, optimizing, and governing reporting and planning solutions within SAP Analytics Cloud (SAC). This role supports enterprise dashboard initiatives, planning models, and governed self-service analytics. The Analytics Engineer partners closely with the Analytics Systems Lead to ensure SAC solutions are scalable, secure, and aligned to enterprise data standards and semantic models.
Responsibilities
This is a fully remote position.
D&H is growing! Join 100 year old Employee-Owned technology distributor, offering end-to-end solutions for today's resellers, retailers, and the clients they serve across the SMB and Consumer markets.
- We are empowered by our employee Co-Owners who provide the industry’s best service, and we promote a collaborative culture.
- We offer an Employee Stock Ownership Plan, 401k, Paid Time Off, Medical, Prescription, Dental and Vision benefits as well as Gym Reimbursement, Work from Home Reimbursement, Employee Purchase Program, Tuition Assistance and much more!
- As a D&H Co-Owner you receive numerous discounts on services.
- We feel strongly about giving back to the community and promoting sustainable, eco-friendly business practices.
We are seeking an Analytics Engineer – Enterprise Analytics for our Data Science & Insights Department. This position is responsible for developing, optimizing, and governing reporting and planning solutions within SAP Analytics Cloud (SAC). This role supports enterprise dashboard initiatives, planning models, and governed self-service analytics. The Analytics Engineer partners closely with the Analytics Systems Lead to ensure SAC solutions are scalable, secure, and aligned to enterprise data standards and semantic models.
Responsibilities
- Designs, builds, and maintains dashboards, stories, and analytic applications within SAP Analytics Cloud.
- Develops SAC data models that align to certified enterprise datasets and semantic standards.
- Supports planning and performance management use cases where applicable.
- Implements role-based access controls and adhere to defined security models.
- Collaborates with SAP BDC/Datasphere and Data Engineering teams to ensure reliable data connectivity.
- Optimizes SAC performance, data refresh strategies, and model efficiency.
- Supports transport, lifecycle management, and controlled content deployment processes.
- Contributes to documentation, standards, and best practices for SAC development.
- Assists in troubleshooting production issues and participate in platform support processes.
- Bachelor’s degree in Information Systems, Data Analytics, Finance Systems, or related field required.
- 3–6 years of experience in analytics engineering, BI development, or enterprise reporting roles required.
- Hands-on experience developing in SAP Analytics Cloud (Stories, Models, Planning, or Applications) required. Experience integrating SAC with SAP Datasphere or other SAP data sources preferred.
- Strong understanding of data modeling concepts and semantic layer principles and working knowledge of SQL and relational data concepts required.
- Experience implementing role-based access and governance within analytics platforms required.
- Strong collaboration skills across technical and business teams and the ability to translate business requirements into scalable analytic solutions required.
- Exposure to enterprise planning or financial performance management workflows, familiarity with Tableau or Power BI environments and experience working in modernization or platform transition initiatives preferred.