Ofertes d'ocupació a Happens

• Nivell d'experiència---
• Tipus de contracteA temps complert
• Publicada21 de juny

Python TSQL Scala Google Ads Kafka Spark Machine Learning

Are you passionate about data, real-time pipelines, and high-impact decision-making? Do you want to build and scale a cutting-edge data platform that transforms how we handle marketing, customer engagement, and personalization?

Our MarTech Data Engineering team bridges the gap between marketing, data, and business strategy, handling high-volume data from various sources, including digital advertising platforms, internal customer insights, and real-time event streams. We’re looking for a Data Engineer to help us build scalable data solutions that power advanced marketing analytics, customer segmentation, and real-time personalization.

What You’ll Do

• Design and Develop Data Pipelines: Build and optimize ETL/ELT processes and data pipelines handling 100M+ changes daily.
• Enable Personalization & Decision Making: Power marketing strategies and customer engagement tools by integrating data from Google Ads, Meta Ads, TikTok, Twitter, and other platforms.
• Model Data for Insights & Reporting: Design clean, structured data models in Snowflake (or similar analytical databases) that fuel campaign analytics, LTV models, and budget optimization.
• Collaborate Across Teams: Work with data analysts, product managers, and marketing teams to translate business needs into scalable data solutions.
• Experiment & Innovate: Introduce new technologies and influence data architecture decisions to push the boundaries of MarTech innovation.
  
  

• Strong experience with ETL, batch, and data pipelines
• Good experience in Python, SQL, and/or Scala
• Experience with Snowflake, BigQuery, or similar analytical databases
• Ability to design and implement report-ready data layers for analytics & BI teams
• Ability to work with marketing and product teams to translate business requirements into data solutions
  
  

• Experience with Airflow or other orchestration tools
• Familiarity with Kafka, Spark, or real-time data processing
• Knowledge of LTV modeling, marketing attribution, and customer segmentation
• Exposure to machine learning pipelines for marketing analytics
  
  

• Work on a high-scale, cutting-edge data platform
• Direct impact on marketing strategy, customer engagement, and revenue growth
• A collaborative, cross-functional environment with data, product, and marketing teams
• Opportunities to introduce new technologies and shape data architecture
• Solve complex, high-volume data challenges in a fast-paced, innovative industry