Lead Data Engineer
Uses CursorAI for intelligent data workflows and automation; ties into AI-assisted data engineering and automation.
About the Role
Lead Data Engineer responsible for designing, building, and maintaining scalable B2B marketing data pipelines and data models to support marketing measurement, targeting, and reporting. The role leads cross-functional engineering efforts, ensures data quality and reliability, and automates enrichment and analytics workflows.
Job Description
Role
Lead Data Engineer on the Marketing Operations & Engineering team focused on expanding and maintaining the data infrastructure for B2B marketing analytics. The role drives engineering efforts to deliver reliable data pipelines, unified data models, automation, and assets that support marketing measurement and planning.
Key Responsibilities
- Design, implement, and maintain robust ETL/data pipelines for ingestion and processing of B2B marketing data from various sources (CRM systems such as Dynamics and Salesforce).
- Lead cross-functional collaboration with marketing, analytics, data science, and product teams to define data requirements and ensure data quality and consistency.
- Develop scalable data models for a unified B2B Data Mart to support targeting, measurement, and planning.
- Automate contact and account data enrichment workflows using third-party providers and internal systems.
- Build and maintain data assets powering dashboards and reporting for marketing performance and engagement metrics.
- Ensure performance, reliability, and security of the B2B data infrastructure.
Requirements
- 8+ years of experience in data engineering with emphasis on B2B marketing data.
- Strong SQL, Python, and Spark skills.
- Experience with data pipeline orchestration tools (examples: Airflow, dbt).
- Experience with CursorAI or similar platforms for intelligent data workflows and automation.
- Hands-on experience with cloud platforms (AWS, Azure, GCP) and cloud analytics environments such as Databricks.
- Familiarity with CRM systems and their data models (Salesforce, Dynamics).
- Understanding of B2B marketing operations, campaign metadata, segmentation, and behavioral analytics.
- Experience collaborating with Data Scientists and BI Engineers.
- Excellent communication skills and ability to explain technical concepts to non-technical stakeholders.
Compensation & Benefits
- U.S. pay range: $133,900 – $242,000 annually (base for non-sales roles; pay varies by location and experience).
- Short-term incentives: Annual Incentive Plan (AIP) for non-sales roles.
- Certain roles may be eligible for long-term incentives in the form of a new hire equity award.
Notes
Removed legal boilerplate and company “About” fluff. State-specific notices and equal employment statements were omitted from the main responsibilities and requirements above.