Data Engineer-

Deine Aufgaben

• Data Engineer, Marketing Technology About Us: Foxit is remaking the way the world interacts with documents through advanced PDF technology and tools. We are a leading global software provider of fast, affordable, and secure PDF solutions that are used by millions of people worldwide. Winner of numerous awards, Foxit has customers in more than 200 countries and global operations. We have a complete product line and an exciting and aggreßive development schedule. Our proven PDF technology is disrupting the status quo establishment and has accelerated our company growth. We are proud to list as customers Google and Amazon, and with your skills and help, we plan to add many more. Foxit has offices all over the world, including locations in the US, Asia, Europe, and Australia. For more information, visit us @ www.foxit.com About the Role We are looking for an experienced Data Engineer to own the data pipelines that power our go-to-market systems. While this role is aligned to the marketing department's priorities, you will work day-to-day within our Busineß Applications & Data Analytics team, following the team's established development standards, architecture patterns, and code review proceßes. This ensures the pipelines you build are consistent with our broader data platform and maintainable by the wider engineering team. Your primary focus will be marketing-related data needs - working closely with demand gen, product marketing, sales operations, and digital teams to understand their requirements, then building and maintaining the pipelines and integrations that deliver on them. This is a hands-on execution role. You will build and operate the data infrastructure that connects our marketing automation platform (HubSpot), CRM (Salesforce), data warehouse (Databricks), licensing system, payment platform, and other source systems. Your work will directly support marketing's ability to segment audiences, measure attribution, and run data-driven campaigns at scale. What You'll Do 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 b