Engineer building and operating data systems for Spotify's marketing initiatives. Contributing to data pipelines and integrations supporting global campaigns like Wrapped.
Responsibilities
build and operate data pipelines that power paid media attribution, audience targeting, and campaign measurement across global marketing platforms
build and operate batch and real-time data pipelines on Google Cloud Platform that process billions of marketing and user events daily at global scale
partner with marketing, analytics, and product teams to instrument data collection, translate requirements, and ensure data quality while operating within legal and regulatory constraints
contribute to integrations with external marketing platforms, supporting reliable audience delivery and suppression workflows
monitor and improve production systems, strengthening reliability, observability, and operational readiness
work within a cross-functional, agile squad to build and own data systems end to end, partnering with marketing, analytics, and insights teams to create solutions aligned with business priorities
collaborate with fellow engineers to design, build, and operate data systems, while contributing to shared standards, tooling, and continuous improvements in how the team works
Requirements
solid experience building and maintaining production data pipelines and systems
familiar with development and deployment within cloud environments (ideally GCP)
fluent in SQL and at least one programming language (Python, Java, or Scala)
experience using cloud data warehouses like BigQuery, Snowflake, or Redshift
understand batch and streaming data processing, ETL/ELT patterns, and data modeling fundamentals
care deeply about data quality, system reliability, and building systems downstream users can trust
value strong engineering practices, including testing, monitoring, and maintainable code
comfortable incorporating GenAI tools like Claude into your development workflow
comfortable working in an agile, product-oriented environment and collaborating across engineering, product, analytics, and marketing
pragmatic, hands-on, and able to balance delivery speed with long-term quality
thrive in ambiguous and fast-changing environments, and know how to make progress even when requirements are evolving
experience with marketing technology ecosystems (attribution platforms, CDPs, ad platforms) is a bonus.
AWS Data Engineer designing data models and supporting data architecture for various clients at EXL. Collaborating to deliver data solutions for improved business outcomes in a hybrid work environment.
Senior Data Engineer at Noda creating scalable data solutions for smarter, sustainable buildings. Collaborating with teams to optimize data for high - performance analytics.
Leading Technology Consulting as Associate Director at Protiviti, focusing on Microsoft Fabric and Databricks. Strengthening client relationships through analytics and mentoring teams in consulting engagements.
Senior Consultant position at Protiviti mentoring teams on data analytics and engineering solutions using Microsoft technologies, enhancing efficiency and client relationship management.
GCP Data Engineer specializing in data governance, architecture, and quality. Collaborates in a hybrid environment across multiple locations in Mexico.
Director of Data Engineering leading data architecture and analytics at Petfolk. Overseeing data infrastructure and managing a data team to drive AI and business intelligence solutions.
Senior Data Engineer managing end - to - end data pipelines with Google Cloud Platform. Collaborating closely with product teams to deliver scalable data solutions in a hybrid setting.
GCP Data Engineer designing, building, and optimising data solutions on Google Cloud Platform. Collaborating with clients to solve complex data challenges and enhance AI capabilities.
Data Engineer developing scalable data solutions across multi - cloud environments for clients. Mentoring junior engineers while ensuring data quality and promoting best practices within the team.