Senior Data Engineer at Merkle | AdTechTalent
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Merkle
Senior Data Engineer
GCP Google Cloud Platform BigQuery Dataflow Dataproc DBT Pub/Sub Cloud Storage Cloud Composer Airflow Cloud SQL SQL Python PySpark Apache Beam ETL ELT Data pipelines Streaming Data engineering AI ML GenAI Vertex AI BigQuery ML Data catalog Metadata CI/CD DevOps Semantic modeling Data product development
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Join Merkle and work on a role built for experienced AdTech operators.
Full job description Seeking a GCP Data Engineer to develop and deliver enterprise data and AI platforms on Google Cloud Platform. Responsibilities include building scalable batch and real-time data pipelines, modernizing legacy workflows, developing reusable data products, and supporting AI/ML data enablement. Work with GCP services such as BigQuery, Dataflow, Dataproc, Pub/Sub, Cloud Storage, Cloud Composer, and Cloud SQL. Implement data quality, schema management, metadata enrichment, and data contracts. Collaborate with analytics and BI teams to improve data usability and support semantic models. Follow coding standards, participate in code reviews, and support operational monitoring and governance. Requires 3-6 years experience in data engineering, strong SQL and Python skills, and hands-on GCP experience. Bachelor’s degree in relevant field required. GCP certifications are a plus.
What you'll do Develop and maintain scalable batch and real-time data pipelines on GCP Build ingestion, transformation, and serving pipelines supporting enterprise analytics and AI use cases Similar jobs
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Assist in modernization of legacy data workflows into cloud-native architectures
Develop reusable and maintainable data engineering components following established architectural standards
Support implementation of event-driven and streaming-based data processing solutions
Contribute to development of reusable and domain-oriented data products
Implement data transformation logic and standardized data models supporting downstream analytics and AI consumption
Support implementation of data quality validations, schema management, metadata enrichment, data contracts, and reusable transformation frameworks
Ensure data pipelines are reliable, scalable, and production-ready
Work with GCP-native services including BigQuery, Dataflow, Dataproc, DBT, Pub/Sub, Cloud Storage, Cloud Composer (Airflow), Cloud SQL
Develop ETL/ELT pipelines and optimize data processing workloads
Support orchestration and scheduling of enterprise data workflows
Monitor and troubleshoot pipeline performance, failures, and operational issues
Support implementation of semantic models and business-friendly data structures for analytics and reporting
Collaborate with analytics and BI teams to improve consistency and usability of enterprise data assets
Assist in development of standardized metrics, dimensions, and reusable reporting datasets
Contribute to metadata and data catalog integration initiatives
Build and optimize AI-ready data pipelines supporting ML and GenAI initiatives
Support feature engineering and data preparation workflows for AI/ML use cases
Assist in integration with Vertex AI, BigQuery ML, vector databases, GenAI frameworks
Contribute to implementation of semantic search and AI-assisted data interaction patterns
Follow established coding standards, architecture guidelines, and DevOps practices
Participate in code reviews, testing, debugging, and performance optimization activities
Collaborate effectively with architects, lead engineers, analysts, and client stakeholders
Contribute to engineering documentation, operational runbooks, and technical knowledge sharing
Continuously learn and adopt modern cloud, data engineering, and AI platform technologies
Support implementation of monitoring, logging, lineage, and observability frameworks
Ensure adherence to enterprise security, governance, and compliance standards
Assist in incident resolution, root cause analysis, and platform stability improvements
Contribute to continuous improvement initiatives for operational excellence and delivery quality Requirements Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field 3–6 years of experience in data engineering and cloud-based data platform development Hands-on experience working with Google Cloud Platform (GCP) data services Strong SQL and Python programming skills Experience developing scalable ETL/ELT pipelines and distributed data processing workflows Understanding of modern data architecture concepts including data lakes, data warehouses, and streaming pipelines Exposure to analytics, AI/ML, or GenAI-enabled data ecosystems preferred Strong analytical, troubleshooting, and problem-solving skills Ability to work collaboratively in Agile and cross-functional delivery teams GCP certifications such as Associate Cloud Engineer or Professional Data Engineer are a plus Tech stack Google Cloud Platform GCP BigQuery Dataflow Dataproc DBT Pub/Sub Cloud Storage Cloud Composer Airflow Cloud SQL SQL Python PySpark Apache Beam Vertex AI BigQuery ML GenAI Data Catalog Git CI/CD
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Company
Merkle Merkle, a dentsu company, powers the experience economy. For more than 35 years, the company has put people at the heart of its approach to digital business transformation. As the only integrated experience consultancy in the world with a heritage in data science and business performance, Merkle delivers holistic, end-to-end experiences that drive growth, engagement, and loyalty. Merkle’s expertise has earned recognition as a “Leader” by top industry analyst firms, in categories such as digital transformation and commerce, experience design, engineering and technology integration, digital marketing, data science, CRM and loyalty, and customer data management. With more than 16,000 employees, Merkle operates in 30+ countries throughout the Americas, EMEA, and APAC.
Industry
Business Consulting and Services
Website
https://www.merkle.com
Posted
2 months ago
Category: Data Science
New York, US • 4 months ago
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