Senior Big Data Engineer

We are looking for aSenior Data Engineerto 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 engagement through the end of **, 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, DV360Experience 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 flexibleA competitive salary and good compensation packagePersonalized career growthProfessional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)Active tech communities with regular knowledge sharingEducation reimbursementMemorable anniversary presentsCorporate events and team buildingsOther location-specific benefitsnot applicable for freelancers

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.

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