Cloud Data Engineer — Snowflake BigQuery Migration

Be | Shaping the Future · Germany · posted today ago

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About this role

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.