Job Closed
This listing is no longer active.
Adaptive SPM for AI-Accelerated Innovation | Modular Solutions, Compounding Value | 30,000+ Customers
Principal GTM Data Engineer – Architect
Location
United States
Posted
97 days ago
Salary
0
Seniority
Lead
Job Description
Principal GTM Data Engineer – Architect
Tempo Software
• Architect and implement the unified GTM data spine across CRM, marketing automation, product telemetry, billing, enrichment providers, partner data, and the warehouse. • Establish identity resolution, deduplication, and source-of-truth logic across systems. • Define canonical schemas that we’ll use to operate the business, enable AI across teams and drive results. • Build scalable ELT/ETL pipelines and orchestration workflows tailored to revenue activation. • Implement governance, lineage, access control, and quality monitoring for GTM data assets. • Partner closely with the BI / enterprise data team to align on shared infrastructure while owning GTM-specific models and activation layers. • Develop and productionize segmentation and scoring models (ICP scoring, ABM prioritization, expansion propensity, trial health, pipeline likelihood). • Apply statistical and machine learning techniques to improve scoring, targeting, routing, and revenue predictability. • Design experimentation and measurement frameworks for GTM programs. • Operationalize predictive outputs directly into GTM systems via agents, reverse ETL, or custom integration (Salesforce workflows, outbound automation, lifecycle programs, ABM platforms, partner programs). • Architect customer and prospect intelligence systems integrating first-party, enrichment, and ecosystem signals. • Develop frameworks for ecosystem intelligence (partner influence, marketplace signals, derived demand). • Enable real-time or near-real-time signal activation to sales and marketing teams. • Design structured data systems that power future AI-driven revenue workflows. • Manage and direct external agency/consulting partners executing against the GTM data roadmap. • Establish architectural standards and technical review processes. • Define the build vs. buy strategy for GTM data systems. • Develop the long-term roadmap for in-house data capability.
Job Requirements
- 10+ years of experience in data engineering, analytics engineering, revenue data, or related leadership roles.
- Demonstrated experience standing up a GTM or revenue data function from the ground up.
- Deep hands-on expertise with modern data stack tools (cloud warehouse, transformation layer, orchestration, reverse ETL).
- Advanced proficiency in SQL and Python.
- Experience applying data science techniques in a GTM or revenue context.
- Experience architecting data systems that power automation and AI workflows.
- Strong understanding of CRM and marketing automation data models.
Benefits
- Remote First work environment
- Unlimited vacation in most of our locations!!
- Great benefits including health, dental, vision and savings plan.
- Perks such as training reimbursement, WFH reimbursement, and more.
- Diverse and dynamic teams with challenging and exciting work.
- An opportunity to have a real impact on our business.
- A great range of social activities (both in person and virtual).
- Optional in person meet-ups and the ability to travel to our international offices
- Employee referral program
- And so much more!
Related Guides
Related Categories
Related Job Pages
More Data Engineer Jobs
Lead Data Engineer
ExavaluDigital Transformation Consulting Leader with expertise in business/ technology advisory and digital platform solutions
• Data Pipeline Engineering: Architect, build, and maintain complex, real-time, and batch data pipelines using Azure Data Factory, Python/PySpark, and Databricks. • Architecture & Modelling: Design and implement modern data warehouse solutions, data models, and data lakes, optimizing for performance and scalability. • Data Ingestion & Integration: Ingest, cleanse, and transform data from diverse sources into usable data structures for analytics. • Security & Governance: Implement security features, including role-based access control (RBAC), data encryption, and governance via Azure Purview.
Data Engineer
ExavaluDigital Transformation Consulting Leader with expertise in business/ technology advisory and digital platform solutions
• Data Pipeline Development: Design, build, and optimize robust ETL/ELT pipelines using Azure Databricks, Spark, and SQL. • Data Processing & Transformation: Utilize Python, PySpark, and SQL to clean, transform, and aggregate complex data for analytics. • Azure Data Lake Management: Manage and optimize data storage and retrieval in Azure Data Lake Storage (ADLS) Gen2. • Delta Lake Implementation: Implement Delta Lake for ACID compliance, data versioning, and high-performance data lake operations. • Integration with Azure Services: Integrate Databricks with Azure Data Factory for orchestration, Azure Synapse Analytics for warehousing, and Azure Key Vault for security. • Performance Optimization: Monitor, troubleshoot, and optimize Databricks clusters and spark jobs to manage costs and performance. • Data Security & Governance: Implement Role-Based Access Control (RBAC), data encryption, and data lineage tracking. • Requirements Collaboration: Work with data scientists and analysts to support machine learning models and business intelligence (BI) reporting.
• Own and architect the end-to-end reporting lifecycle in the diamond matching project • Inherit a replicated production environment • Transform raw Python application data into a high-performance analytics layer • Bridge the gap between backend data structures and business-ready visualizations
• Deliver end-to-end data migration activities across SAP ECC and HR platforms • Extract, transform, and load data using ETL tools (SAP BODS preferred) • Perform data mapping, cleansing, validation, and reconciliation • Develop and execute SQL queries for data analysis and validation • Support testing cycles including SIT and UAT • Work closely with HR, IT, and functional stakeholders • Document data migration processes and technical specifications • Ensure data integrity, compliance, and audit readiness
