• Assist in the design, build, testing, deployment, and production support of core data warehouse and analytics solutions • Perform initial data exploration steps such as profiling, understanding data quality, binning, pivoting, and summarizing • Consult with data SMEs to understand and address data quality issues • Support the design, build, test, and deployment of data warehouse solutions • Provide modeling analysis and develop data models according to specifications and standards • Support the data cleaning, integration, and transformation of data according to the defined target data model

Lead architectural evolution of the data platform, optimize data lake architecture for performance and governance, and establish foundational data management capabilities to support advanced analytics and data science initiatives.

• Build and maintain data ingestion pipelines from APIs and other data sources • Write efficient Python and SQL for data transformation and processing • Support ETL/ELT workflows, microservices and ensure timely data availability • Troubleshoot pipeline failures and assist in performance improvements • Assist in ingestion and modeling of data from Meta Ads and similar platforms • Help create datasets for campaign performance reporting and lead funnel tracking • Work with marketing and analytics teams to understand data requirements • Help translate business needs into data queries and datasets • Implement basic data validation checks • Monitor pipelines and resolve data issues • Maintain documentation for pipelines and datasets

• Designing scalable data architecture • Driving business outcomes (revenue, lead quality, conversion efficiency) • Owning how data is used, trusted and acted upon • Design, build, and maintain robust data pipelines for social marketing and product data sources (APIs, event streams, batch systems) • Develop scalable ETL/ELT workflows / microservices using Python and SQL • Ensure high data quality, reliability and observability across pipelines • Optimize data models for analytics and reporting use cases • Own ingestion and modeling of data from Meta Ads (Facebook) and other digital marketing platforms • Build datasets that support: Campaign performance tracking, Lead funnel analysis, Attribution and conversion tracking • Translate business requirements from marketing, growth and product teams into scalable data solutions • Define success metrics tied to revenue and performance • Enable self-serve analytics through well-structured datasets • Implement validation checks, monitoring and alerting for pipelines • Ensure consistency across different marketing data sources • Maintain clear documentation of data models and pipelines • Work closely with marketing, growth, and analytics teams to understand real-world use cases • Own key use cases such as: Lead funnel optimization, Campaign attribution, Revenue reporting and forecasting