GCP Data Engineering Manager

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee the comprehensive migration of enterprise data platforms from AWS to GCP.

• Evaluate current AWS architecture, data pipelines, workloads, dependencies, and operational workflows.

• Establish the target GCP architecture, migration roadmap, phases, dependencies, risks, and rollback strategies.

• Facilitate architecture reviews and technical design discussions.

• Design and implement scalable enterprise GCP data platforms, including Data Lake and Lakehouse architectures.

• Create frameworks for batch and real-time ETL/ELT, streaming ingestion, transformation, and consumption.

• Develop BigQuery data models, including partitioning, clustering, and scalable analytics consumption models.

• Set standards for data governance, quality, lineage, metadata, ownership, and security.

• Direct Terraform-based infrastructure automation and CI/CD deployment practices.

• Enhance GCP performance, scalability, SLAs, and cloud cost efficiency.

• Mentor and provide technical guidance to Data Engineers, Senior Data Engineers, and Technical Leads.

• Monitor engineering progress, risks, dependencies, and delivery milestones.

• Serve as the primary technical contact for stakeholders based in the US.

• Partner with Business, Product, Data Science, BI, and DevOps teams.

• Convert business requirements into scalable technical solutions and convey architecture decisions, risks, timelines, and trade-offs.

⛳️ Requirements

• 15+ years of experience in Data Engineering, Data Architecture, or Cloud Engineering.

• 5+ years of practical GCP Data Engineering experience.

• Extensive hands-on experience with AWS Data Engineering and Architecture.

• Demonstrated experience in AWS-to-GCP migration projects.

• Strong background in designing enterprise Data Lake and Lakehouse platforms.

• In-depth knowledge of AWS and GCP service mapping, as well as cloud migration patterns.

• Expert-level SQL skills and strong proficiency in Python/PySpark.

• Robust experience in data modeling and data warehousing.

• Familiarity with Terraform and CI/CD practices.

• Experience in managing and mentoring data engineering teams.

• Excellent communication skills and experience collaborating with US-based stakeholders.

• Ability to evaluate AWS workloads, define GCP target architecture, and lead migration through to production implementation.

• Proficiency in BigQuery, Google Cloud Storage, Pub/Sub, Dataflow/Apache Beam, Cloud Composer/Airflow, Dataproc/Spark, Cloud Monitoring, and Cloud Logging.

• Knowledge of AWS services such as S3, Glue, Glue Data Quality, Redshift, Athena, Step Functions, DMS, Lake Formation, and IAM.

• Experience with ETL/ELT, CDC, batch and streaming data processing, and event-driven architecture.

• Familiarity with Data Lakehouse, Medallion Architecture, dimensional data modeling, and multi-tenant architectures.

• Understanding of schema-on-read, schema-on-write, data lineage, metadata management, and data governance.

• Experience with dbt, Terraform, Git/GitHub, Cloud Build, CI/CD, data quality frameworks, and OpenLineage.

• Hands-on experience as a GCP Engineering Manager is preferred; current Senior/Lead Data Engineer profiles are not suitable.

🏝️ Benefits

• Flexible remote work environment.

• Exposure to global enterprise customers.

• Collaborative, innovation-driven engineering culture.

• Continuous learning and certification opportunities.

• Opportunity to spearhead large-scale AWS-to-GCP cloud transformation initiatives.

• Engage in enterprise Data Lakehouse and analytics modernization projects.