Build and maintain scalable GCP data pipelines, BigQuery data models, enterprise semantic layers, and CI/CD workflows for a modernized marketing data platform. Rebuild legacy pipelines, support DataHub adoption, enforce data quality, optimize performance and costs, and enable secure multi-brand marketing reporting. Collaborate with product, Martech, analytics, and data engineering teams.
We are looking for a Senior Data Engineer to join a strategic marketing technology (Martech) transformation initiative for a large enterprise organization. The project focuses on modernizing the client's marketing data platform, rebuilding data pipelines, and improving marketing attribution across multiple business brands.
As part of a dedicated data engineering team, you will help build a scalable, cloud-native data platform on Google Cloud Platform (GCP), enabling better visibility into marketing performance and supporting data-driven decision making. This is a long-term engagement through the end of 2026, working closely with the client's Data Engineering, Product, and Martech teams.
Responsibilities:
- Design, develop, and maintain scalable data pipelines on Google Cloud Platform (GCP).
- Build and optimize data models in BigQuery to support analytics and marketing reporting.
- Rebuild legacy marketing data pipelines following modern engineering best practices and enterprise standards.
- Contribute to the development of a canonical enterprise data model and semantic data layer.
- Support the implementation and adoption of DataHub as the enterprise data catalog.
- Develop automated CI/CD pipelines for data engineering workflows and enforce coding and data quality standards.
- Ensure proper data isolation between multiple business brands while enabling consolidated reporting where appropriate.
- Collaborate closely with Product Managers, Martech specialists, Analytics teams, and other data engineers to deliver business value.
- Optimize data processing performance, reliability, monitoring, and cost efficiency.
Required Qualifications:
- 5+ years of experience as a Data Engineer.
- Strong hands-on experience with Google Cloud Platform (GCP).
- Advanced experience with BigQuery.
- Strong SQL and Python development skills.
- Experience designing and implementing modern ELT/ETL pipelines.
- Solid understanding of dimensional modeling, semantic modeling, and enterprise data architecture.
- Experience building production-grade CI/CD pipelines for data platforms.
- Familiarity with Git and modern software engineering best practices.
- Strong communication skills and ability to work within cross-functional teams.
- Upper-Intermediate or higher English.
Nice to Have:
- Experience with marketing technology (Martech) platforms and marketing attribution.
- Hands-on experience integrating: Google Ads, Google Analytics (GA4), Search Ads 360 (SA360), Campaign Manager 360, DV360
- Experience with DataHub or similar data catalog solutions.
- Experience implementing semantic layers for analytics platforms.
- Understanding of multi-brand or multi-tenant data architectures.
- Experience modernizing legacy data platforms and rebuilding pipelines from scratch.
We offer*:
- Flexible working format - remote, office-based or flexible
- A competitive salary and good compensation package
- Personalized career growth
- Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
- Active tech communities with regular knowledge sharing
- Education reimbursement
- Memorable anniversary presents
- Corporate events and team buildings
- Other location-specific benefits
*not applicable for freelancers
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