TEAM OVERVIEW

KKR’s Technology team is responsible for building and supporting the firm’s technological foundation. Technology is regarded as a key business enabler at KKR and is an important accelerator for global scale and business process transformation. We drive a culture of excellence through efficient workflow automation, the democratization of data, and the strategic implementation of emerging technologies to consistently serve our business needs.

POSITION SUMMARY

The Senior Data Analyst will serve as the expert for Marketing data, ensuring that marketing data is sourced, engineered, structured, modeled, integrated, and analytics ready. This role focuses on building, maintaining, and validating marketing data assets across systems like Marketo, Salesforce, Snowflake, and web platforms. This individual is expected to understand Marketing data across KKR and work closely with digital, and marketing stakeholders to unify data sources, engineer data, optimize data flows, and enable meaningful insights that drive marketing performance and ROI.

RESPONSIBILITIES

Data Management and Integration

• Design, maintain, and enhance data pipelines connecting Marketo, Salesforce, web analytics, and other marketing systems to Snowflake or centralized data environments.
• Collaborate across business teams to help translate data requirements to (data) engineering specs, validate ETL logic, and ensure marketing data is structured and modeled for analytics.
• Create and maintain data dictionaries, source-to-target mappings, and documentation for marketing datasets.
• Identify correlations between various data sets/sources to design the analytics Marketing data model for KKR
• Proactively identify and resolve data issues; establish data validation checks and reconciliation processes.

Data Analysis and Modeling

• Query, join, and transform large datasets using SQL (and optionally Python/R) to enable campaign, channel, and funnel analysis.
• Develop and maintain key marketing metrics such as conversion rate, engagement rate, ROI, and lead-to-opportunity ratios.
• Support creation of multi-touch attribution and funnel models to measure campaign influence across channels.
• Analyze campaign data to uncover trends, identify performance drivers, and inform targeting and segmentation strategies.
• Support forecasting of marketing performance and lead flow using historical data and predictive indicators.

Partnership and Collaboration

• Serve as the data SME for Marketing Analytics, partnering with the Marketing team to translate business questions into data requirements.
• Collaborate cross-functionally with the Data Hub, Digital Analytics, and Marketing Operations teams to streamline data availability and integrity.
• Act as a liaison between marketing and technical teams to ensure consistent metric definitions and business logic.

Enablement and Reporting Support

• Enable reporting automation and data accessibility by preparing well-structured tables and views.
• Partner with analysts and stakeholders to interpret results and guide data-driven marketing strategies.

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