Data Engineering Architect – Salesforce Sales & Service Analytics
Hi,
We are seeking a senior data leader with deep functional expertise in Salesforce Sales and Service domains to own the enterprise data model, metrics, and analytical outcomes supporting Sales, Service, and Customer Operations.
This role is business‑first and data‑centric. The successful candidate understands how Salesforce Sales Cloud and Service Cloud data is generated, evolves over time, and is consumed by business teams, and ensures analytics accurately reflect operational reality.
Snowflake serves as the enterprise analytics platform, but Salesforce domain mastery and functional data expertise are the primary requirements for success in this role.
Core Responsibilities
Salesforce Sales & Service Data Ownership
· Act as the data owner and architect for Salesforce Sales and Service domains.
- Own Sales data including leads, accounts, opportunities, pipeline, bookings, revenue, forecasting, and CPQ (if applicable).
- Own Service data including cases, case lifecycle, SLAs, backlog, escalations, and service performance metrics.
- Define and govern enterprise‑wide KPI and metric definitions across Sales and Service.
- Ensure alignment between Salesforce operational definitions and analytics/reporting outputs.
- Own cross‑functional metrics spanning Sales, Service, and the customer lifecycle (e.g., customer health, renewals, churn).
Business‑Driven Data Modeling
· Design Salesforce‑centric analytical data models that accurately reflect Sales and Service processes.
- Model sales stage progression, pipeline history, and forecast changes over time.
- Model service case lifecycle, SLA compliance, backlog aging, and resolution metrics.
- Handle Salesforce‑specific complexities such as slowly changing dimensions (ownership, territory, account hierarchies).
- Ensure data models support operational dashboards, executive reporting, and advanced analytics.
Analytics Enablement & Business Partnership
· Partner closely with Sales Operations, Service Operations, Revenue Operations, Finance, and Analytics teams.
- Translate business questions into trusted, reusable analytical datasets.
- Identify data quality issues or Salesforce process gaps impacting reporting and drive remediation.
- Enable self‑service analytics through well‑documented, certified data products.
Technical Responsibilities (Enabling Focus)
· Architect and govern Salesforce data ingestion and modeling on Snowflake.
- Guide ELT/ETL strategies for Salesforce objects such as Opportunities, Accounts, Activities, Cases, and Entitlements.
- Ensure reconciliation and auditability between Salesforce, Finance, and analytics layers.
- Define data access, security, and governance aligned with Salesforce usage patterns.
- Partner with data engineering teams on scalability, performance, and cost efficiency.
Required Experience & Skills
Salesforce Sales & Service Domain Expertise (Must‑Have)
· Extensive hands‑on experience working with Salesforce Sales Cloud and Service Cloud data.
- Strong understanding of sales pipeline management, forecasting, and revenue reporting.
- Strong understanding of service case workflows, SLAs, backlog management, and service performance measurement.
- Experience working directly with Sales Operations and Service Operations teams.
- Ability to identify when Salesforce configuration or process issues cause reporting inconsistencies.
Data & Analytics Expertise
· 10+ years working with business‑critical analytical data.
- Proven experience defining KPIs, metrics, and semantic models for Sales and Service domains.
- Strong SQL and analytical skills to validate business logic and data outcomes.
- Experience supporting BI and analytics platforms such as Tableau, Power BI, or MicroStrategy.
Platform Experience
· Experience using Snowflake as an enterprise analytics platform.
- Understanding of modern ELT/ETL and cloud data architecture concepts.
- Familiarity with data governance, lineage, and access control best practices.
Leadership & Collaboration
· Acts as a bridge between business stakeholders and technical teams.
- Comfortable challenging requirements using business and data context.
- Mentors engineers and analysts on Salesforce data nuances and business meaning.
- Strong communicator able to explain complex Salesforce data behavior to non‑technical leaders.
Thanks,
Ampera Talent Team
Shubham Vishwakarma
Full Stack Developer - Averlon
About Ampera Technologies
About
At Ampera Technologies, we empower businesses with cutting-edge data analytics, quality assurance, and data engineering solutions
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