As a part of the Revenue Operations team, the Senior GTM Data Engineer will be a strategic partner to the sales and data orchestration data teams, creating business-ready tables, leveraging data-driven insights to shape and optimize sales strategies and campaigns. This role is integral to optimizing the data infrastructure that supports sales analytics, ensuring data integrity, and enabling scalable and efficient access to sales data. The Senior GTM Data Engineer will focus on designing scalable pipelines, translating complex data into meaningful narratives that inform decision-making and drive business growth, and guiding data strategy through deep analysis and advanced data visualization. With a strong understanding of data normalization strategies, attribution methodologies, sales and partner metrics, the customer lifecycle, and industry best practices, this individual will collaborate closely with cross-functional teams to ensure that data-driven insights are at the forefront of sales initiatives. The role requires a proactive approach to enhancing sales performance through data manipulation, exploration, reporting, and strategic recommendations.

Key Responsibilities

• Serve as primary liaison with cross functional partners such as GTM & Commercialization, Marketing Technology & Operations, Enterprise Data, Finance/BI, Product & Technology, Sales, Operations, and Partners to integrate, govern, and standardize sales data across GTM systems (CRM, Snowflake, BigQuery, Salesforce, Marketo/Pardot, GA4, and other sales technologies).

• Own the design, development and maintenance of scalable data models and architecture in Snowflake, BigQuery, DBT, and related tools to ensure clean, business-ready, and well-documented data assets to power revenue reporting, forecastingand analytics.

• Build and optimize data pipelines and ELT workflows in Snowflake, ensuring reliability, performance, and cost efficiency.

• Define, standardize, and maintain governing sales data infrastructure, ensuring consistency of key metrics, taxonomies, and architecture across global sales teams.

• Partner with Finance, BI, Sales Operations and Marketing Operations to develop, refine, and operationalize sales attribution methodologies that connect pipeline and revenue outcomes.

• Monitor,validate, andoptimizedata flows and integrations,establishingQA processes, anomaly detection, and documentation to ensure accuracy and trustworthiness of data.

• Lead data stewardship efforts, supporting data governance, compliance, and integration standards across platforms and global teams.

• Extract, refine, and manage complex campaign and audience lists for segmentation, targeting, and activation; ensure accuracy, compliance, and alignment with ICP definitions andsales objectives

• Build, analyze, andoptimizeaudience segments across platforms (e.g., Salesforce, ZoomInfo, CDPs) to support global sales campaigns and demand generation efforts.

• Conduct deep-dive data analysis, combining multiple systems and large datasets to generate actionable insights on customer behavior, lifecycle performance, andsalesROI.

• Build andmaintainadvanced dashboards and reports in Power BI and other visualization platforms, ensuring accessibility, accuracy, and usability for sales stakeholders and executives.

• Support ad hoc analysis requests, executive scorecards, and MBR/QBR reporting to evaluate sales performance and business impact.

• Provide elevated team leadership by mentoring and supporting colleagues on complex data pulls, insights analysis, dashboard design, segmentation, and systems requirements.

• Act as a cross-functional liaison, bridging revenue operations with enterprise data, technology, and business stakeholders to align on data strategy, requirements, and execution.

• Proactively explore new technologies, tools, and best practices to advance sales and marketing data operations, segmentation, and performance reporting capabilities.

Requirements:

• Bachelor’s degree in Business, Statistics, Data Analytics, DataScienceora relatedfield.

• 6+ years of experience in data analysis, reporting, or business intelligence, preferably within a sales context.

• Strong understanding of sales metrics, customer lifecycle, and best sales practices.

• Experience with data visualization tools such as Tableau, Power BI, Looker, or similar platforms.

• Familiarity with querying and analyzing data from data warehouses (e.g., Snowflake,BigQuery) and advanced knowledge of data tools like Tableau,PowerBI, Looker, Salesforce Data Studio, Excel, and Power Query.

• Proficiency in SQL and Python for querying databases and preparing data for analysis.

• Proficiencyin data analysis techniques, including data cleansing, joining, and exploratory analysis.

• Experience with data visualization best practices and creating engaging visual reports and dashboards.

• Strong analytical and problem-solving skills, with attention to detail.

• Ability to communicate complex data concepts clearly to non-technical stakeholders.

• Experience with attribution modeling and multi-touch revenue analysis

• Familiarity with marketing automation platforms and CRM systems (e.g., Salesforce, Marketo, Pardot,etc).

• Knowledge of forecasting techniques and sales analytics frameworks.

• Familiarity with global consent management regulations (e.g., GDPR, CCPA) and data privacy best practices.

• Proficiencyin data extraction, manipulation, and analysis using tools like SQL, Python, Excel, or data visualization platforms (e.g., Tableau, Power BI).

• Experience working with segmentation tools and platforms (e.g., Salesforce, CDP, Google Analytics,RingLead, ZoomInfo, Equifax,etc).

• Strong analytical and problem-solving skills witha keenattention to detail.

• Excellent communication skills to collaborate with cross-functional teams and present insights effectively.

• Ability to work independently and prioritize tasks in a fast-paced environment.

• Understanding ofmarketing strategies, lead management processes, and audience targeting best practices.

• Familiarity with B2B marketing and revenue generation strategies.

• Preferred: Experience with Customer Data Platforms (CDP) and advanced segmentation techniques.

• Preferred: Background in working with or supporting multi-regional sales teams.

• **Data Visualization experience,is a plus. Leveraging best practices and creating engaging & interactive visual reports and dashboards.

• ** Experience with Customer Data Platforms (CDPs) and data integration concepts, is a plus

• **Experience with data science tools and techniques, such as R or Python, is a plus.