Foxit - Data Engineer-Marketing Technology

• Data Pipeline Development & Operations • Design, build, and maintain ETL/ELT pipelines, building upon and further optimizing our existing medallion architecture (Bronze → Silver → Gold) to move data between source systems (Salesforce CRM, HubSpot, NetSuite, Stripe, DealHub, LMS) and our Databricks data warehouse. • Build pipelines using PySpark and SQL in Databricks notebooks, following established development standards for naming, project structure, and layer-appropriate transformations. • Own the data sync layer between Databricks and HubSpot — enrichment flows inbound to HubSpot (license status, renewal dates, subscription state, firmographic data) and marketing engagement data flowing back to Databricks (email events, workflow enrollment, lifecycle changes). • Build and maintain Exchange layer pipelines that curate data for external system consumption, formatting and validating data to meet target system requirements. • Build and maintain scheduled batch jobs and event-driven integrations using APIs (REST, webhooks, OAuth). • Monitor pipeline health, set up alerting for failures and data quality degradation, and own incident response when syncs break. • Maintain documentation of data flows, integration architecture, and troubleshooting runbooks. • Data Modeling & Quality • Build and maintain dimensional models in Databricks (fact tables, dimension tables, bridge tables) following our data warehouse object type definitions and naming standards. • Work in collaboration with stakeholders and data analysts to build curated, business-ready tables and datamarts that apply business logic, KPI calculations, and aggregations optimized for analytics and campaign activation. • Implement identity resolution and deduplication logic to produce unified customer profiles from multiple source systems. • Establish data validation rules, quality checks, and monitoring to ensure accuracy and freshness of data flowing into marketing systems. • Normalize disparate data sources into clean centralized schemas with proper type enforcement, deduplication, and null handling. • Marketing Data & Segmentation Support • Ensure the data infrastructure supports audience segmentation, including firmographic, behavioral, and engagement signals. • Build the data layer that powers lifecycle marketing - triggered campaigns, dynamic journey branching, and personalization based on enriched customer profiles. • Support marketing and demand gen teams with reliable, accessible data for building audience targets in HubSpot. • Maintain data flows for email deliverability, subscription management, and suppression list synchronization. • Integration Development • Build and maintain API integrations between marketing, sales, and operational systems using Python and SQL. • Implement field-level transformation logic, sync orchestration, and error handling for system-to-system data flows. • Support website form and lead capture data flows - ensuring clean handoff from web properties into HubSpot and Databricks. • Work with third-party enrichment providers (firmographic, intent, technographic) to integrate enrichment data into automated workflows. • Reporting & Attribution • Build and maintain the data infrastructure that supports campaign attribution, channel performance analysis, and funnel reporting. • Ensure accurate data for conversion analytics, lead source tracking, and marketing ROI measurement. • Support centralized reporting by routing marketing engagement data back into Databricks for cross-functional analysis.