Cloud Data Engineer — Snowflake BigQuery Migration
BE München, Brandenburg, Germany
Marketing Services · 51-200 employees
About the role
Lead large-scale enterprise data platform modernization and migration initiatives from Snowflake to BigQuery. Design, develop, and maintain high-performance data pipelines while establishing enterprise-grade governance and operational standards.
What they look for
Requirements
Requires a minimum of 5 years of experience in data engineering and a Google Cloud Professional Data Engineer certification. Proven track record in migrating large-scale data warehouses and expertise in BigQuery architecture is mandatory.
Full description
Role Overview
We are seeking an experienced Senior Data Engineer / Data Migration Architect to lead large-scale enterprise data platform modernization initiatives on Google Cloud. The ideal candidate will have a proven track record of migrating large-scale data warehouses (hundreds of terabytes) to BigQuery, designing high-performance data architectures, and delivering production-grade analytics platforms. Experience migrating from Snowflake to BigQuery is highly preferred; candidates with migration experience from other platforms must demonstrate strong exposure to Snowflake through other engagements.
Key Responsibilities
Data Platform Modernization & Migration
- Lead the assessment, design, and execution of large-scale data warehouse migrations to BigQuery, including environments exceeding hundreds of terabytes of data.
- Define migration strategies, data models, governance frameworks, and performance optimization approaches.
- Drive modernization initiatives that improve scalability, reliability, cost efficiency, and operational excellence.
- Collaborate with stakeholders to ensure seamless migration with minimal business disruption.
Data Engineering & Architecture
- Design, develop, and maintain high-performance data pipelines supporting both batch and streaming workloads.
- Architect secure, scalable, and highly available data lakes and data warehouse solutions on Google Cloud Platform.
- Establish enterprise-grade data processing frameworks, integration patterns, and governance standards.
- Ensure data quality, observability, lineage, and operational reliability across the data ecosystem.
BigQuery Engineering & Optimization
- Serve as the technical expert for BigQuery architecture, performance optimization, and best practices.
- Implement advanced SQL optimization techniques to improve query performance and reduce operational costs.
- Design efficient partitioning, clustering, storage, and workload management strategies.
- Optimize data processing pipelines for performance, scalability, and cost efficiency.
Cloud Architecture & Delivery Leadership
- Design and implement enterprise cloud architectures aligned with business and technical requirements.
- Lead customer-facing projects from solution design through implementation and production deployment.
- Provide technical leadership, mentoring, and architectural guidance to engineering teams.
- Support client workshops, architecture reviews, and strategic roadmap discussions.
DevOps, Automation & Platform Engineering
- Automate infrastructure provisioning and platform deployment using Infrastructure as Code (IaC) practices.
- Design and maintain CI/CD pipelines supporting data platform development and deployment.
- Implement monitoring, alerting, testing, and operational automation capabilities.
- Promote DevOps best practices across development and operations teams.
Cross-Functional Collaboration
- Partner closely with Data Scientists, Data Analysts, Software Engineers, and Business Stakeholders to deliver end-to-end data solutions.
- Support advanced analytics, machine learning, and data-driven decision-making initiatives.
- Translate business requirements into scalable technical solutions and actionable delivery plans.
Mandatory Qualifications
- Minimum 5 years of experience designing, developing, and delivering high-performance data pipelines for both streaming and batch processing workloads.
- Proven experience migrating large-scale enterprise data warehouses to BigQuery, preferably from Snowflake.
- Experience with data warehouse environments measured in hundreds of terabytes.
- Strong expertise in BigQuery architecture, administration, optimization, and operations.
- Demonstrated experience building and maintaining secure, reliable, and scalable data lakes and data warehouses on Google Cloud Platform.
- Proven ability to design enterprise cloud solutions and lead customer projects through successful delivery.
- Hands-on experience with infrastructure automation, DevOps practices, and CI/CD implementation.
- Google Cloud Professional Data Engineer certification.
- Fluent English communication skills, both written and verbal.
Preferred Qualifications
- Fluent German language skills.
- Experience in technical consulting and customer-facing advisory roles.
- Advanced SQL tuning expertise focused on performance optimization and cost efficiency.
- Experience designing and implementing streaming data pipelines with a strong understanding of event delivery semantics and distributed processing concepts.
- Proven experience building production-grade, internet-scale Big Data solutions using managed cloud services.
- Hands-on experience with Snowflake architectures and migration methodologies.
- Experience with Ab Initio is considered an advantage.
- Strong collaboration experience with Data Scientists, Data Analysts, and Software Engineering teams in enterprise environments.
Preferred Technical Expertise
- Google Cloud Platform (GCP)
- BigQuery
- Data Lake and Data Warehouse Architecture
- Snowflake
- Data Migration & Modernization Programs
- Streaming Data Platforms
- Infrastructure as Code (IaC)
- CI/CD and DevOps Tooling
- SQL Performance Tuning
- Data Governance, Security, and Compliance
- Enterprise Data Architecture
- Analytics and Machine Learning Enablement
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